MERS-CoV spillover at the camel-human interface
Identifieur interne : 001228 ( Pmc/Corpus ); précédent : 001227; suivant : 001229MERS-CoV spillover at the camel-human interface
Auteurs : Gytis Dudas ; Luiz Max Carvalho ; Andrew Rambaut ; Trevor BedfordSource :
- eLife [ 2050-084X ] ; ????.
Abstract
Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic virus from camels causing significant mortality and morbidity in humans in the Arabian Peninsula. The epidemiology of the virus remains poorly understood, and while case-based and seroepidemiological studies have been employed extensively throughout the epidemic, viral sequence data have not been utilised to their full potential. Here, we use existing MERS-CoV sequence data to explore its phylodynamics in two of its known major hosts, humans and camels. We employ structured coalescent models to show that long-term MERS-CoV evolution occurs exclusively in camels, whereas humans act as a transient, and ultimately terminal host. By analysing the distribution of human outbreak cluster sizes and zoonotic introduction times, we show that human outbreaks in the Arabian peninsula are driven by seasonally varying zoonotic transfer of viruses from camels. Without heretofore unseen evolution of host tropism, MERS-CoV is unlikely to become endemic in humans.
Url:
DOI: 10.7554/eLife.31257
PubMed: 29336306
PubMed Central: 5777824
Links to Exploration step
PMC:5777824Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">MERS-CoV spillover at the camel-human interface</title><author><name sortKey="Dudas, Gytis" sort="Dudas, Gytis" uniqKey="Dudas G" first="Gytis" last="Dudas">Gytis Dudas</name><affiliation><nlm:aff id="aff1"><institution content-type="dept">Vaccine and Infectious Disease Division</institution><institution>Fred Hutchinson Cancer Research Center</institution><addr-line>Seattle</addr-line><country>United States</country></nlm:aff></affiliation></author><author><name sortKey="Carvalho, Luiz Max" sort="Carvalho, Luiz Max" uniqKey="Carvalho L" first="Luiz Max" last="Carvalho">Luiz Max Carvalho</name><affiliation><nlm:aff id="aff2"><institution content-type="dept">Institute of Evolutionary Biology</institution><institution>University of Edinburgh</institution><addr-line>Edinburgh</addr-line><country>United Kingdom</country></nlm:aff></affiliation></author><author><name sortKey="Rambaut, Andrew" sort="Rambaut, Andrew" uniqKey="Rambaut A" first="Andrew" last="Rambaut">Andrew Rambaut</name><affiliation><nlm:aff id="aff2"><institution content-type="dept">Institute of Evolutionary Biology</institution><institution>University of Edinburgh</institution><addr-line>Edinburgh</addr-line><country>United Kingdom</country></nlm:aff></affiliation><affiliation><nlm:aff id="aff3"><institution content-type="dept">Fogarty International Center</institution><institution>National Institutes of Health</institution><addr-line>Bethesda</addr-line><country>United States</country></nlm:aff></affiliation></author><author><name sortKey="Bedford, Trevor" sort="Bedford, Trevor" uniqKey="Bedford T" first="Trevor" last="Bedford">Trevor Bedford</name><affiliation><nlm:aff id="aff1"><institution content-type="dept">Vaccine and Infectious Disease Division</institution><institution>Fred Hutchinson Cancer Research Center</institution><addr-line>Seattle</addr-line><country>United States</country></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">29336306</idno><idno type="pmc">5777824</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5777824</idno><idno type="RBID">PMC:5777824</idno><idno type="doi">10.7554/eLife.31257</idno><date when="????">????</date><idno type="wicri:Area/Pmc/Corpus">001228</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">001228</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">MERS-CoV spillover at the camel-human interface</title><author><name sortKey="Dudas, Gytis" sort="Dudas, Gytis" uniqKey="Dudas G" first="Gytis" last="Dudas">Gytis Dudas</name><affiliation><nlm:aff id="aff1"><institution content-type="dept">Vaccine and Infectious Disease Division</institution><institution>Fred Hutchinson Cancer Research Center</institution><addr-line>Seattle</addr-line><country>United States</country></nlm:aff></affiliation></author><author><name sortKey="Carvalho, Luiz Max" sort="Carvalho, Luiz Max" uniqKey="Carvalho L" first="Luiz Max" last="Carvalho">Luiz Max Carvalho</name><affiliation><nlm:aff id="aff2"><institution content-type="dept">Institute of Evolutionary Biology</institution><institution>University of Edinburgh</institution><addr-line>Edinburgh</addr-line><country>United Kingdom</country></nlm:aff></affiliation></author><author><name sortKey="Rambaut, Andrew" sort="Rambaut, Andrew" uniqKey="Rambaut A" first="Andrew" last="Rambaut">Andrew Rambaut</name><affiliation><nlm:aff id="aff2"><institution content-type="dept">Institute of Evolutionary Biology</institution><institution>University of Edinburgh</institution><addr-line>Edinburgh</addr-line><country>United Kingdom</country></nlm:aff></affiliation><affiliation><nlm:aff id="aff3"><institution content-type="dept">Fogarty International Center</institution><institution>National Institutes of Health</institution><addr-line>Bethesda</addr-line><country>United States</country></nlm:aff></affiliation></author><author><name sortKey="Bedford, Trevor" sort="Bedford, Trevor" uniqKey="Bedford T" first="Trevor" last="Bedford">Trevor Bedford</name><affiliation><nlm:aff id="aff1"><institution content-type="dept">Vaccine and Infectious Disease Division</institution><institution>Fred Hutchinson Cancer Research Center</institution><addr-line>Seattle</addr-line><country>United States</country></nlm:aff></affiliation></author></analytic><series><title level="j">eLife</title><idno type="eISSN">2050-084X</idno><imprint><date when="????">????</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic virus from camels causing significant mortality and morbidity in humans in the Arabian Peninsula. The epidemiology of the virus remains poorly understood, and while case-based and seroepidemiological studies have been employed extensively throughout the epidemic, viral sequence data have not been utilised to their full potential. Here, we use existing MERS-CoV sequence data to explore its phylodynamics in two of its known major hosts, humans and camels. We employ structured coalescent models to show that long-term MERS-CoV evolution occurs exclusively in camels, whereas humans act as a transient, and ultimately terminal host. By analysing the distribution of human outbreak cluster sizes and zoonotic introduction times, we show that human outbreaks in the Arabian peninsula are driven by seasonally varying zoonotic transfer of viruses from camels. Without heretofore unseen evolution of host tropism, MERS-CoV is unlikely to become endemic in humans.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Abdallah, H" uniqKey="Abdallah H">H Abdallah</name></author><author><name sortKey="Faye, B" uniqKey="Faye B">B Faye</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Adney, Dr" uniqKey="Adney D">DR Adney</name></author><author><name sortKey="Van Doremalen, N" uniqKey="Van Doremalen N">N van Doremalen</name></author><author><name sortKey="Brown, Vr" uniqKey="Brown V">VR Brown</name></author><author><name sortKey="Bushmaker, T" uniqKey="Bushmaker T">T Bushmaker</name></author><author><name sortKey="Scott, D" uniqKey="Scott D">D Scott</name></author><author><name sortKey="De Wit, E" uniqKey="De Wit E">E de Wit</name></author><author><name sortKey="Bowen, Ra" uniqKey="Bowen R">RA Bowen</name></author><author><name sortKey="Munster, Vj" uniqKey="Munster V">VJ Munster</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ali, Ma" uniqKey="Ali M">MA Ali</name></author><author><name sortKey="Shehata, Mm" uniqKey="Shehata M">MM Shehata</name></author><author><name sortKey="Gomaa, Mr" uniqKey="Gomaa M">MR Gomaa</name></author><author><name sortKey="Kandeil, A" uniqKey="Kandeil A">A Kandeil</name></author><author><name sortKey="El Shesheny, R" uniqKey="El Shesheny R">R El-Shesheny</name></author><author><name sortKey="Kayed, As" uniqKey="Kayed A">AS Kayed</name></author><author><name sortKey="El Taweel, An" uniqKey="El Taweel A">AN El-Taweel</name></author><author><name sortKey="Atea, M" uniqKey="Atea M">M Atea</name></author><author><name sortKey="Hassan, N" uniqKey="Hassan N">N Hassan</name></author><author><name sortKey="Bagato, O" uniqKey="Bagato O">O Bagato</name></author><author><name sortKey="Moatasim, Y" uniqKey="Moatasim Y">Y Moatasim</name></author><author><name sortKey="Mahmoud, Sh" uniqKey="Mahmoud S">SH Mahmoud</name></author><author><name sortKey="Kutkat, O" uniqKey="Kutkat O">O Kutkat</name></author><author><name sortKey="Maatouq, Am" uniqKey="Maatouq A">AM Maatouq</name></author><author><name sortKey="Osman, A" uniqKey="Osman A">A Osman</name></author><author><name sortKey="Mckenzie, Pp" uniqKey="Mckenzie P">PP McKenzie</name></author><author><name sortKey="Webby, Rj" uniqKey="Webby R">RJ Webby</name></author><author><name sortKey="Kayali, G" uniqKey="Kayali G">G Kayali</name></author><author><name sortKey="Systematic, Kg" uniqKey="Systematic K">KG Systematic</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Almutairi, Se" uniqKey="Almutairi S">SE Almutairi</name></author><author><name sortKey="Boujenane, I" uniqKey="Boujenane I">I Boujenane</name></author><author><name sortKey="Musaad, A" uniqKey="Musaad A">A Musaad</name></author><author><name sortKey="Awad Acharari, F" uniqKey="Awad Acharari F">F Awad-Acharari</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Antia, R" uniqKey="Antia R">R Antia</name></author><author><name sortKey="Regoes, Rr" uniqKey="Regoes R">RR Regoes</name></author><author><name sortKey="Koella, Jc" uniqKey="Koella J">JC Koella</name></author><author><name sortKey="Bergstrom, Ct" uniqKey="Bergstrom C">CT Bergstrom</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Assiri, A" uniqKey="Assiri A">A Assiri</name></author><author><name sortKey="Al Tawfiq, Ja" uniqKey="Al Tawfiq J">JA Al-Tawfiq</name></author><author><name sortKey="Al Rabeeah, Aa" uniqKey="Al Rabeeah A">AA Al-Rabeeah</name></author><author><name sortKey="Al Rabiah, Fa" uniqKey="Al Rabiah F">FA Al-Rabiah</name></author><author><name sortKey="Al Hajjar, S" uniqKey="Al Hajjar S">S Al-Hajjar</name></author><author><name sortKey="Al Barrak, A" uniqKey="Al Barrak A">A Al-Barrak</name></author><author><name sortKey="Flemban, H" uniqKey="Flemban H">H Flemban</name></author><author><name sortKey="Al Nassir, Wn" uniqKey="Al Nassir W">WN Al-Nassir</name></author><author><name sortKey="Balkhy, Hh" uniqKey="Balkhy H">HH Balkhy</name></author><author><name sortKey="Al Hakeem, Rf" uniqKey="Al Hakeem R">RF Al-Hakeem</name></author><author><name sortKey="Makhdoom, Hq" uniqKey="Makhdoom H">HQ Makhdoom</name></author><author><name sortKey="Zumla, Ai" uniqKey="Zumla A">AI Zumla</name></author><author><name sortKey="Memish, Za" uniqKey="Memish Z">ZA Memish</name></author><author><name sortKey="Epidemiological, Mza" uniqKey="Epidemiological M">MZA Epidemiological</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Assiri, A" uniqKey="Assiri A">A Assiri</name></author><author><name sortKey="Mcgeer, A" uniqKey="Mcgeer A">A McGeer</name></author><author><name sortKey="Perl, Tm" uniqKey="Perl T">TM Perl</name></author><author><name sortKey="Price, Cs" uniqKey="Price C">CS Price</name></author><author><name sortKey="Al Rabeeah, Aa" uniqKey="Al Rabeeah A">AA Al Rabeeah</name></author><author><name sortKey="Cummings, Da" uniqKey="Cummings D">DA Cummings</name></author><author><name sortKey="Alabdullatif, Zn" uniqKey="Alabdullatif Z">ZN Alabdullatif</name></author><author><name sortKey="Assad, M" uniqKey="Assad M">M Assad</name></author><author><name sortKey="Almulhim, A" uniqKey="Almulhim A">A Almulhim</name></author><author><name sortKey="Makhdoom, H" uniqKey="Makhdoom H">H Makhdoom</name></author><author><name sortKey="Madani, H" uniqKey="Madani H">H Madani</name></author><author><name sortKey="Alhakeem, R" uniqKey="Alhakeem R">R Alhakeem</name></author><author><name sortKey="Al Tawfiq, Ja" uniqKey="Al Tawfiq J">JA Al-Tawfiq</name></author><author><name sortKey="Cotten, M" uniqKey="Cotten M">M Cotten</name></author><author><name sortKey="Watson, Sj" uniqKey="Watson S">SJ Watson</name></author><author><name sortKey="Kellam, P" uniqKey="Kellam P">P Kellam</name></author><author><name sortKey="Zumla, Ai" uniqKey="Zumla A">AI Zumla</name></author><author><name sortKey="Memish, Za" uniqKey="Memish Z">ZA Memish</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Assiri, Am" uniqKey="Assiri A">AM Assiri</name></author><author><name sortKey="Biggs, Hm" uniqKey="Biggs H">HM Biggs</name></author><author><name sortKey="Abedi, Gr" uniqKey="Abedi G">GR Abedi</name></author><author><name sortKey="Lu, X" uniqKey="Lu X">X Lu</name></author><author><name sortKey="Bin Saeed, A" uniqKey="Bin Saeed A">A Bin Saeed</name></author><author><name sortKey="Abdalla, O" uniqKey="Abdalla O">O Abdalla</name></author><author><name sortKey="Mohammed, M" uniqKey="Mohammed M">M Mohammed</name></author><author><name sortKey="Al Abdely, Hm" uniqKey="Al Abdely H">HM Al-Abdely</name></author><author><name sortKey="Algarni, Hs" uniqKey="Algarni H">HS Algarni</name></author><author><name sortKey="Alhakeem, Rf" uniqKey="Alhakeem R">RF Alhakeem</name></author><author><name sortKey="Almasri, Mm" uniqKey="Almasri M">MM Almasri</name></author><author><name sortKey="Alsharef, Aa" uniqKey="Alsharef A">AA Alsharef</name></author><author><name sortKey="Nooh, R" uniqKey="Nooh R">R Nooh</name></author><author><name sortKey="Erdman, Dd" uniqKey="Erdman D">DD Erdman</name></author><author><name sortKey="Gerber, Si" uniqKey="Gerber S">SI Gerber</name></author><author><name sortKey="Watson, Jt" uniqKey="Watson J">JT Watson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Assiri, Am" uniqKey="Assiri A">AM Assiri</name></author><author><name sortKey="Midgley, Cm" uniqKey="Midgley C">CM Midgley</name></author><author><name sortKey="Abedi, Gr" uniqKey="Abedi G">GR Abedi</name></author><author><name sortKey="Bin Saeed, A" uniqKey="Bin Saeed A">A Bin Saeed</name></author><author><name sortKey="Almasri, Mm" uniqKey="Almasri M">MM Almasri</name></author><author><name sortKey="Lu, X" uniqKey="Lu X">X Lu</name></author><author><name sortKey="Al Abdely, Hm" uniqKey="Al Abdely H">HM Al-Abdely</name></author><author><name sortKey="Abdalla, O" uniqKey="Abdalla O">O Abdalla</name></author><author><name sortKey="Mohammed, M" uniqKey="Mohammed M">M Mohammed</name></author><author><name sortKey="Algarni, Hs" uniqKey="Algarni H">HS Algarni</name></author><author><name sortKey="Alhakeem, Rf" uniqKey="Alhakeem R">RF Alhakeem</name></author><author><name sortKey="Sakthivel, Sk" uniqKey="Sakthivel S">SK Sakthivel</name></author><author><name sortKey="Nooh, R" uniqKey="Nooh R">R Nooh</name></author><author><name sortKey="Alshayab, Z" uniqKey="Alshayab Z">Z Alshayab</name></author><author><name sortKey="Alessa, M" uniqKey="Alessa M">M Alessa</name></author><author><name sortKey="Srinivasamoorthy, G" uniqKey="Srinivasamoorthy G">G Srinivasamoorthy</name></author><author><name sortKey="Alqahtani, Sy" uniqKey="Alqahtani S">SY AlQahtani</name></author><author><name sortKey="Kheyami, A" uniqKey="Kheyami A">A Kheyami</name></author><author><name sortKey="Hajomar, Wh" uniqKey="Hajomar W">WH HajOmar</name></author><author><name sortKey="Banaser, Tm" uniqKey="Banaser T">TM Banaser</name></author><author><name sortKey="Esmaeel, A" uniqKey="Esmaeel A">A Esmaeel</name></author><author><name sortKey="Hall, Aj" uniqKey="Hall A">AJ Hall</name></author><author><name sortKey="Curns, At" uniqKey="Curns A">AT Curns</name></author><author><name sortKey="Tamin, A" uniqKey="Tamin A">A Tamin</name></author><author><name sortKey="Alsharef, Aa" uniqKey="Alsharef A">AA Alsharef</name></author><author><name sortKey="Erdman, D" uniqKey="Erdman D">D Erdman</name></author><author><name sortKey="Watson, Jt" uniqKey="Watson J">JT Watson</name></author><author><name sortKey="Gerber, Si" uniqKey="Gerber S">SI Gerber</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Azhar, Ei" uniqKey="Azhar E">EI Azhar</name></author><author><name sortKey="El Kafrawy, Sa" uniqKey="El Kafrawy S">SA El-Kafrawy</name></author><author><name sortKey="Farraj, Sa" uniqKey="Farraj S">SA Farraj</name></author><author><name sortKey="Hassan, Am" uniqKey="Hassan A">AM Hassan</name></author><author><name sortKey="Al Saeed, Ms" uniqKey="Al Saeed M">MS Al-Saeed</name></author><author><name sortKey="Hashem, Am" uniqKey="Hashem A">AM Hashem</name></author><author><name sortKey="Madani, Ta" uniqKey="Madani T">TA Madani</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bedford, T" uniqKey="Bedford T">T Bedford</name></author><author><name sortKey="Cobey, S" uniqKey="Cobey S">S Cobey</name></author><author><name sortKey="Pascual, M" uniqKey="Pascual M">M Pascual</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Blumberg, S" uniqKey="Blumberg S">S Blumberg</name></author><author><name sortKey="Lloyd Smith, Jo" uniqKey="Lloyd Smith J">JO Lloyd-Smith</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Boni, Mf" uniqKey="Boni M">MF Boni</name></author><author><name sortKey="Posada, D" uniqKey="Posada D">D Posada</name></author><author><name sortKey="Feldman, Mw" uniqKey="Feldman M">MW Feldman</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bouckaert, R" uniqKey="Bouckaert R">R Bouckaert</name></author><author><name sortKey="Heled, J" uniqKey="Heled J">J Heled</name></author><author><name sortKey="Kuhnert, D" uniqKey="Kuhnert D">D Kühnert</name></author><author><name sortKey="Vaughan, T" uniqKey="Vaughan T">T Vaughan</name></author><author><name sortKey="Wu, Ch" uniqKey="Wu C">CH Wu</name></author><author><name sortKey="Xie, D" uniqKey="Xie D">D Xie</name></author><author><name sortKey="Suchard, Ma" uniqKey="Suchard M">MA Suchard</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author><author><name sortKey="Drummond, Aj" uniqKey="Drummond A">AJ Drummond</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Briese, T" uniqKey="Briese T">T Briese</name></author><author><name sortKey="Mishra, N" uniqKey="Mishra N">N Mishra</name></author><author><name sortKey="Jain, K" uniqKey="Jain K">K Jain</name></author><author><name sortKey="Zalmout, Is" uniqKey="Zalmout I">IS Zalmout</name></author><author><name sortKey="Jabado, Oj" uniqKey="Jabado O">OJ Jabado</name></author><author><name sortKey="Karesh, Wb" uniqKey="Karesh W">WB Karesh</name></author><author><name sortKey="Daszak, P" uniqKey="Daszak P">P Daszak</name></author><author><name sortKey="Mohammed, Ob" uniqKey="Mohammed O">OB Mohammed</name></author><author><name sortKey="Alagaili, An" uniqKey="Alagaili A">AN Alagaili</name></author><author><name sortKey="Lipkin, Wi" uniqKey="Lipkin W">WI Lipkin</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bruen, Tc" uniqKey="Bruen T">TC Bruen</name></author><author><name sortKey="Philippe, H" uniqKey="Philippe H">H Philippe</name></author><author><name sortKey="Bryant, D" uniqKey="Bryant D">D Bryant</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Carpenter, B" uniqKey="Carpenter B">B Carpenter</name></author><author><name sortKey="Gelman, A" uniqKey="Gelman A">A Gelman</name></author><author><name sortKey="Hoffman, M" uniqKey="Hoffman M">M Hoffman</name></author><author><name sortKey="Lee, D" uniqKey="Lee D">D Lee</name></author><author><name sortKey="Goodrich, B" uniqKey="Goodrich B">B Goodrich</name></author><author><name sortKey="Betancourt, M" uniqKey="Betancourt M">M Betancourt</name></author><author><name sortKey="Brubaker, Ma" uniqKey="Brubaker M">MA Brubaker</name></author><author><name sortKey="Guo, J" uniqKey="Guo J">J Guo</name></author><author><name sortKey="Li, P" uniqKey="Li P">P Li</name></author><author><name sortKey="Riddell, A" uniqKey="Riddell A">A Riddell</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Cauchemez, S" uniqKey="Cauchemez S">S Cauchemez</name></author><author><name sortKey="Nouvellet, P" uniqKey="Nouvellet P">P Nouvellet</name></author><author><name sortKey="Cori, A" uniqKey="Cori A">A Cori</name></author><author><name sortKey="Jombart, T" uniqKey="Jombart T">T Jombart</name></author><author><name sortKey="Garske, T" uniqKey="Garske T">T Garske</name></author><author><name sortKey="Clapham, H" uniqKey="Clapham H">H Clapham</name></author><author><name sortKey="Moore, S" uniqKey="Moore S">S Moore</name></author><author><name sortKey="Mills, Hl" uniqKey="Mills H">HL Mills</name></author><author><name sortKey="Salje, H" uniqKey="Salje H">H Salje</name></author><author><name sortKey="Collins, C" uniqKey="Collins C">C Collins</name></author><author><name sortKey="Rodriquez Barraquer, I" uniqKey="Rodriquez Barraquer I">I Rodriquez-Barraquer</name></author><author><name sortKey="Riley, S" uniqKey="Riley S">S Riley</name></author><author><name sortKey="Truelove, S" uniqKey="Truelove S">S Truelove</name></author><author><name sortKey="Algarni, H" uniqKey="Algarni H">H Algarni</name></author><author><name sortKey="Alhakeem, R" uniqKey="Alhakeem R">R Alhakeem</name></author><author><name sortKey="Alharbi, K" uniqKey="Alharbi K">K AlHarbi</name></author><author><name sortKey="Turkistani, A" uniqKey="Turkistani A">A Turkistani</name></author><author><name sortKey="Aguas, Rj" uniqKey="Aguas R">RJ Aguas</name></author><author><name sortKey="Cummings, Da" uniqKey="Cummings D">DA Cummings</name></author><author><name sortKey="Van Kerkhove, Md" uniqKey="Van Kerkhove M">MD Van Kerkhove</name></author><author><name sortKey="Donnelly, Ca" uniqKey="Donnelly C">CA Donnelly</name></author><author><name sortKey="Lessler, J" uniqKey="Lessler J">J Lessler</name></author><author><name sortKey="Fraser, C" uniqKey="Fraser C">C Fraser</name></author><author><name sortKey="Al Barrak, A" uniqKey="Al Barrak A">A Al-Barrak</name></author><author><name sortKey="Ferguson, Nm" uniqKey="Ferguson N">NM Ferguson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Chen, X" uniqKey="Chen X">X Chen</name></author><author><name sortKey="Chughtai, Aa" uniqKey="Chughtai A">AA Chughtai</name></author><author><name sortKey="Dyda, A" uniqKey="Dyda A">A Dyda</name></author><author><name sortKey="Macintyre, Cr" uniqKey="Macintyre C">CR MacIntyre</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Chu, Dk" uniqKey="Chu D">DK Chu</name></author><author><name sortKey="Poon, Ll" uniqKey="Poon L">LL Poon</name></author><author><name sortKey="Gomaa, Mm" uniqKey="Gomaa M">MM Gomaa</name></author><author><name sortKey="Shehata, Mm" uniqKey="Shehata M">MM Shehata</name></author><author><name sortKey="Perera, Ra" uniqKey="Perera R">RA Perera</name></author><author><name sortKey="Abu Zeid, D" uniqKey="Abu Zeid D">D Abu Zeid</name></author><author><name sortKey="El Rifay, As" uniqKey="El Rifay A">AS El Rifay</name></author><author><name sortKey="Siu, Ly" uniqKey="Siu L">LY Siu</name></author><author><name sortKey="Guan, Y" uniqKey="Guan Y">Y Guan</name></author><author><name sortKey="Webby, Rj" uniqKey="Webby R">RJ Webby</name></author><author><name sortKey="Ali, Ma" uniqKey="Ali M">MA Ali</name></author><author><name sortKey="Peiris, M" uniqKey="Peiris M">M Peiris</name></author><author><name sortKey="Kayali, G" uniqKey="Kayali G">G Kayali</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Corman, Vm" uniqKey="Corman V">VM Corman</name></author><author><name sortKey="Jores, J" uniqKey="Jores J">J Jores</name></author><author><name sortKey="Meyer, B" uniqKey="Meyer B">B Meyer</name></author><author><name sortKey="Younan, M" uniqKey="Younan M">M Younan</name></author><author><name sortKey="Liljander, A" uniqKey="Liljander A">A Liljander</name></author><author><name sortKey="Said, My" uniqKey="Said M">MY Said</name></author><author><name sortKey="Gluecks, I" uniqKey="Gluecks I">I Gluecks</name></author><author><name sortKey="Lattwein, E" uniqKey="Lattwein E">E Lattwein</name></author><author><name sortKey="Bosch, Bj" uniqKey="Bosch B">BJ Bosch</name></author><author><name sortKey="Drexler, Jf" uniqKey="Drexler J">JF Drexler</name></author><author><name sortKey="Bornstein, S" uniqKey="Bornstein S">S Bornstein</name></author><author><name sortKey="Drosten, C" uniqKey="Drosten C">C Drosten</name></author><author><name sortKey="Muller, Ma" uniqKey="Muller M">MA Müller</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Cotten, M" uniqKey="Cotten M">M Cotten</name></author><author><name sortKey="Watson, Sj" uniqKey="Watson S">SJ Watson</name></author><author><name sortKey="Kellam, P" uniqKey="Kellam P">P Kellam</name></author><author><name sortKey="Al Rabeeah, Aa" uniqKey="Al Rabeeah A">AA Al-Rabeeah</name></author><author><name sortKey="Makhdoom, Hq" uniqKey="Makhdoom H">HQ Makhdoom</name></author><author><name sortKey="Assiri, A" uniqKey="Assiri A">A Assiri</name></author><author><name sortKey="Al Tawfiq, Ja" uniqKey="Al Tawfiq J">JA Al-Tawfiq</name></author><author><name sortKey="Alhakeem, Rf" uniqKey="Alhakeem R">RF Alhakeem</name></author><author><name sortKey="Madani, H" uniqKey="Madani H">H Madani</name></author><author><name sortKey="Alrabiah, Fa" uniqKey="Alrabiah F">FA AlRabiah</name></author><author><name sortKey="Al Hajjar, S" uniqKey="Al Hajjar S">S Al Hajjar</name></author><author><name sortKey="Al Nassir, Wn" uniqKey="Al Nassir W">WN Al-nassir</name></author><author><name sortKey="Albarrak, A" uniqKey="Albarrak A">A Albarrak</name></author><author><name sortKey="Flemban, H" uniqKey="Flemban H">H Flemban</name></author><author><name sortKey="Balkhy, Hh" uniqKey="Balkhy H">HH Balkhy</name></author><author><name sortKey="Alsubaie, S" uniqKey="Alsubaie S">S Alsubaie</name></author><author><name sortKey="Palser, Al" uniqKey="Palser A">AL Palser</name></author><author><name sortKey="Gall, A" uniqKey="Gall A">A Gall</name></author><author><name sortKey="Bashford Rogers, R" uniqKey="Bashford Rogers R">R Bashford-Rogers</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author><author><name sortKey="Zumla, Ai" uniqKey="Zumla A">AI Zumla</name></author><author><name sortKey="Memish, Za" uniqKey="Memish Z">ZA Memish</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Cotten, M" uniqKey="Cotten M">M Cotten</name></author><author><name sortKey="Watson, Sj" uniqKey="Watson S">SJ Watson</name></author><author><name sortKey="Zumla, Ai" uniqKey="Zumla A">AI Zumla</name></author><author><name sortKey="Makhdoom, Hq" uniqKey="Makhdoom H">HQ Makhdoom</name></author><author><name sortKey="Palser, Al" uniqKey="Palser A">AL Palser</name></author><author><name sortKey="Ong, Sh" uniqKey="Ong S">SH Ong</name></author><author><name sortKey="Al Rabeeah, Aa" uniqKey="Al Rabeeah A">AA Al Rabeeah</name></author><author><name sortKey="Alhakeem, Rf" uniqKey="Alhakeem R">RF Alhakeem</name></author><author><name sortKey="Assiri, A" uniqKey="Assiri A">A Assiri</name></author><author><name sortKey="Al Tawfiq, Ja" uniqKey="Al Tawfiq J">JA Al-Tawfiq</name></author><author><name sortKey="Albarrak, A" uniqKey="Albarrak A">A Albarrak</name></author><author><name sortKey="Barry, M" uniqKey="Barry M">M Barry</name></author><author><name sortKey="Shibl, A" uniqKey="Shibl A">A Shibl</name></author><author><name sortKey="Alrabiah, Fa" uniqKey="Alrabiah F">FA Alrabiah</name></author><author><name sortKey="Hajjar, S" uniqKey="Hajjar S">S Hajjar</name></author><author><name sortKey="Balkhy, Hh" uniqKey="Balkhy H">HH Balkhy</name></author><author><name sortKey="Flemban, H" uniqKey="Flemban H">H Flemban</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author><author><name sortKey="Kellam, P" uniqKey="Kellam P">P Kellam</name></author><author><name sortKey="Memish, Za" uniqKey="Memish Z">ZA Memish</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="De Maio, N" uniqKey="De Maio N">N De Maio</name></author><author><name sortKey="Wu, Ch" uniqKey="Wu C">CH Wu</name></author><author><name sortKey="O Reilly, Km" uniqKey="O Reilly K">KM O'Reilly</name></author><author><name sortKey="Wilson, D" uniqKey="Wilson D">D Wilson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Drosten, C" uniqKey="Drosten C">C Drosten</name></author><author><name sortKey="Muth, D" uniqKey="Muth D">D Muth</name></author><author><name sortKey="Corman, Vm" uniqKey="Corman V">VM Corman</name></author><author><name sortKey="Hussain, R" uniqKey="Hussain R">R Hussain</name></author><author><name sortKey="Al Masri, M" uniqKey="Al Masri M">M Al Masri</name></author><author><name sortKey="Hajomar, W" uniqKey="Hajomar W">W HajOmar</name></author><author><name sortKey="Landt, O" uniqKey="Landt O">O Landt</name></author><author><name sortKey="Assiri, A" uniqKey="Assiri A">A Assiri</name></author><author><name sortKey="Eckerle, I" uniqKey="Eckerle I">I Eckerle</name></author><author><name sortKey="Al Shangiti, A" uniqKey="Al Shangiti A">A Al Shangiti</name></author><author><name sortKey="Al Tawfiq, Ja" uniqKey="Al Tawfiq J">JA Al-Tawfiq</name></author><author><name sortKey="Albarrak, A" uniqKey="Albarrak A">A Albarrak</name></author><author><name sortKey="Zumla, A" uniqKey="Zumla A">A Zumla</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author><author><name sortKey="Memish, Za" uniqKey="Memish Z">ZA Memish</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Drosten, C" uniqKey="Drosten C">C Drosten</name></author><author><name sortKey="Seilmaier, M" uniqKey="Seilmaier M">M Seilmaier</name></author><author><name sortKey="Corman, Vm" uniqKey="Corman V">VM Corman</name></author><author><name sortKey="Hartmann, W" uniqKey="Hartmann W">W Hartmann</name></author><author><name sortKey="Scheible, G" uniqKey="Scheible G">G Scheible</name></author><author><name sortKey="Sack, S" uniqKey="Sack S">S Sack</name></author><author><name sortKey="Guggemos, W" uniqKey="Guggemos W">W Guggemos</name></author><author><name sortKey="Kallies, R" uniqKey="Kallies R">R Kallies</name></author><author><name sortKey="Muth, D" uniqKey="Muth D">D Muth</name></author><author><name sortKey="Junglen, S" uniqKey="Junglen S">S Junglen</name></author><author><name sortKey="Muller, Ma" uniqKey="Muller M">MA Müller</name></author><author><name sortKey="Haas, W" uniqKey="Haas W">W Haas</name></author><author><name sortKey="Guberina, H" uniqKey="Guberina H">H Guberina</name></author><author><name sortKey="Rohnisch, T" uniqKey="Rohnisch T">T Röhnisch</name></author><author><name sortKey="Schmid Wendtner, M" uniqKey="Schmid Wendtner M">M Schmid-Wendtner</name></author><author><name sortKey="Aldabbagh, S" uniqKey="Aldabbagh S">S Aldabbagh</name></author><author><name sortKey="Dittmer, U" uniqKey="Dittmer U">U Dittmer</name></author><author><name sortKey="Gold, H" uniqKey="Gold H">H Gold</name></author><author><name sortKey="Graf, P" uniqKey="Graf P">P Graf</name></author><author><name sortKey="Bonin, F" uniqKey="Bonin F">F Bonin</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author><author><name sortKey="Wendtner, Cm" uniqKey="Wendtner C">CM Wendtner</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Drummond, Aj" uniqKey="Drummond A">AJ Drummond</name></author><author><name sortKey="Ho, Sy" uniqKey="Ho S">SY Ho</name></author><author><name sortKey="Phillips, Mj" uniqKey="Phillips M">MJ Phillips</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Drummond, Aj" uniqKey="Drummond A">AJ Drummond</name></author><author><name sortKey="Suchard, Ma" uniqKey="Suchard M">MA Suchard</name></author><author><name sortKey="Xie, D" uniqKey="Xie D">D Xie</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Dudas, G" uniqKey="Dudas G">G Dudas</name></author><author><name sortKey="Bedford, T" uniqKey="Bedford T">T Bedford</name></author><author><name sortKey="Lycett, S" uniqKey="Lycett S">S Lycett</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Dudas, G" uniqKey="Dudas G">G Dudas</name></author><author><name sortKey="Carvalho, Lm" uniqKey="Carvalho L">LM Carvalho</name></author><author><name sortKey="Bedford, T" uniqKey="Bedford T">T Bedford</name></author><author><name sortKey="Tatem, Aj" uniqKey="Tatem A">AJ Tatem</name></author><author><name sortKey="Baele, G" uniqKey="Baele G">G Baele</name></author><author><name sortKey="Faria, Nr" uniqKey="Faria N">NR Faria</name></author><author><name sortKey="Park, Dj" uniqKey="Park D">DJ Park</name></author><author><name sortKey="Ladner, Jt" uniqKey="Ladner J">JT Ladner</name></author><author><name sortKey="Arias, A" uniqKey="Arias A">A Arias</name></author><author><name sortKey="Asogun, D" uniqKey="Asogun D">D Asogun</name></author><author><name sortKey="Bielejec, F" uniqKey="Bielejec F">F Bielejec</name></author><author><name sortKey="Caddy, Sl" uniqKey="Caddy S">SL Caddy</name></author><author><name sortKey="Cotten, M" uniqKey="Cotten M">M Cotten</name></author><author><name sortKey="D Ambrozio, J" uniqKey="D Ambrozio J">J D'Ambrozio</name></author><author><name sortKey="Dellicour, S" uniqKey="Dellicour S">S Dellicour</name></author><author><name sortKey="Di Caro, A" uniqKey="Di Caro A">A Di Caro</name></author><author><name sortKey="Diclaro, Jw" uniqKey="Diclaro J">JW Diclaro</name></author><author><name sortKey="Duraffour, S" uniqKey="Duraffour S">S Duraffour</name></author><author><name sortKey="Elmore, Mj" uniqKey="Elmore M">MJ Elmore</name></author><author><name sortKey="Fakoli, Ls" uniqKey="Fakoli L">LS Fakoli</name></author><author><name sortKey="Faye, O" uniqKey="Faye O">O Faye</name></author><author><name sortKey="Gilbert, Ml" uniqKey="Gilbert M">ML Gilbert</name></author><author><name sortKey="Gevao, Sm" uniqKey="Gevao S">SM Gevao</name></author><author><name sortKey="Gire, S" uniqKey="Gire S">S Gire</name></author><author><name sortKey="Gladden Young, A" uniqKey="Gladden Young A">A Gladden-Young</name></author><author><name sortKey="Gnirke, A" uniqKey="Gnirke A">A Gnirke</name></author><author><name sortKey="Goba, A" uniqKey="Goba A">A Goba</name></author><author><name sortKey="Grant, Ds" uniqKey="Grant D">DS Grant</name></author><author><name sortKey="Haagmans, Bl" uniqKey="Haagmans B">BL Haagmans</name></author><author><name sortKey="Hiscox, Ja" uniqKey="Hiscox J">JA Hiscox</name></author><author><name sortKey="Jah, U" uniqKey="Jah U">U Jah</name></author><author><name sortKey="Kugelman, Jr" uniqKey="Kugelman J">JR Kugelman</name></author><author><name sortKey="Liu, D" uniqKey="Liu D">D Liu</name></author><author><name sortKey="Lu, J" uniqKey="Lu J">J Lu</name></author><author><name sortKey="Malboeuf, Cm" uniqKey="Malboeuf C">CM Malboeuf</name></author><author><name sortKey="Mate, S" uniqKey="Mate S">S Mate</name></author><author><name sortKey="Matthews, Da" uniqKey="Matthews D">DA Matthews</name></author><author><name sortKey="Matranga, Cb" uniqKey="Matranga C">CB Matranga</name></author><author><name sortKey="Meredith, Lw" uniqKey="Meredith L">LW Meredith</name></author><author><name sortKey="Qu, J" uniqKey="Qu J">J Qu</name></author><author><name sortKey="Quick, J" uniqKey="Quick J">J Quick</name></author><author><name sortKey="Pas, Sd" uniqKey="Pas S">SD Pas</name></author><author><name sortKey="Phan, Mvt" uniqKey="Phan M">MVT Phan</name></author><author><name sortKey="Pollakis, G" uniqKey="Pollakis G">G Pollakis</name></author><author><name sortKey="Reusken, Cb" uniqKey="Reusken C">CB Reusken</name></author><author><name sortKey="Sanchez Lockhart, M" uniqKey="Sanchez Lockhart M">M Sanchez-Lockhart</name></author><author><name sortKey="Schaffner, Sf" uniqKey="Schaffner S">SF Schaffner</name></author><author><name sortKey="Schieffelin, Js" uniqKey="Schieffelin J">JS Schieffelin</name></author><author><name sortKey="Sealfon, Rs" uniqKey="Sealfon R">RS Sealfon</name></author><author><name sortKey="Simon Loriere, E" uniqKey="Simon Loriere E">E Simon-Loriere</name></author><author><name sortKey="Smits, Sl" uniqKey="Smits S">SL Smits</name></author><author><name sortKey="Stoecker, K" uniqKey="Stoecker K">K Stoecker</name></author><author><name sortKey="Thorne, L" uniqKey="Thorne L">L Thorne</name></author><author><name sortKey="Tobin, Ea" uniqKey="Tobin E">EA Tobin</name></author><author><name sortKey="Vandi, Ma" uniqKey="Vandi M">MA Vandi</name></author><author><name sortKey="Watson, Sj" uniqKey="Watson S">SJ Watson</name></author><author><name sortKey="West, K" uniqKey="West K">K West</name></author><author><name sortKey="Whitmer, S" uniqKey="Whitmer S">S Whitmer</name></author><author><name sortKey="Wiley, Mr" uniqKey="Wiley M">MR Wiley</name></author><author><name sortKey="Winnicki, Sm" uniqKey="Winnicki S">SM Winnicki</name></author><author><name sortKey="Wohl, S" uniqKey="Wohl S">S Wohl</name></author><author><name sortKey="Wolfel, R" uniqKey="Wolfel R">R Wölfel</name></author><author><name sortKey="Yozwiak, Nl" uniqKey="Yozwiak N">NL Yozwiak</name></author><author><name sortKey="Andersen, Kg" uniqKey="Andersen K">KG Andersen</name></author><author><name sortKey="Blyden, So" uniqKey="Blyden S">SO Blyden</name></author><author><name sortKey="Bolay, F" uniqKey="Bolay F">F Bolay</name></author><author><name sortKey="Carroll, Mw" uniqKey="Carroll M">MW Carroll</name></author><author><name sortKey="Dahn, B" uniqKey="Dahn B">B Dahn</name></author><author><name sortKey="Diallo, B" uniqKey="Diallo B">B Diallo</name></author><author><name sortKey="Formenty, P" uniqKey="Formenty P">P Formenty</name></author><author><name sortKey="Fraser, C" uniqKey="Fraser C">C Fraser</name></author><author><name sortKey="Gao, Gf" uniqKey="Gao G">GF Gao</name></author><author><name sortKey="Garry, Rf" uniqKey="Garry R">RF Garry</name></author><author><name sortKey="Goodfellow, I" uniqKey="Goodfellow I">I Goodfellow</name></author><author><name sortKey="Gunther, S" uniqKey="Gunther S">S Günther</name></author><author><name sortKey="Happi, Ct" uniqKey="Happi C">CT Happi</name></author><author><name sortKey="Holmes, Ec" uniqKey="Holmes E">EC Holmes</name></author><author><name sortKey="Kargbo, B" uniqKey="Kargbo B">B Kargbo</name></author><author><name sortKey="Keita, S" uniqKey="Keita S">S Keïta</name></author><author><name sortKey="Kellam, P" uniqKey="Kellam P">P Kellam</name></author><author><name sortKey="Koopmans, Mpg" uniqKey="Koopmans M">MPG Koopmans</name></author><author><name sortKey="Kuhn, Jh" uniqKey="Kuhn J">JH Kuhn</name></author><author><name sortKey="Loman, Nj" uniqKey="Loman N">NJ Loman</name></author><author><name sortKey="Magassouba, N" uniqKey="Magassouba N">N Magassouba</name></author><author><name sortKey="Naidoo, D" uniqKey="Naidoo D">D Naidoo</name></author><author><name sortKey="Nichol, St" uniqKey="Nichol S">ST Nichol</name></author><author><name sortKey="Nyenswah, T" uniqKey="Nyenswah T">T Nyenswah</name></author><author><name sortKey="Palacios, G" uniqKey="Palacios G">G Palacios</name></author><author><name sortKey="Pybus, Og" uniqKey="Pybus O">OG Pybus</name></author><author><name sortKey="Sabeti, Pc" uniqKey="Sabeti P">PC Sabeti</name></author><author><name sortKey="Sall, A" uniqKey="Sall A">A Sall</name></author><author><name sortKey="Stroher, U" uniqKey="Stroher U">U Ströher</name></author><author><name sortKey="Wurie, I" uniqKey="Wurie I">I Wurie</name></author><author><name sortKey="Suchard, Ma" uniqKey="Suchard M">MA Suchard</name></author><author><name sortKey="Lemey, P" uniqKey="Lemey P">P Lemey</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Dudas, G" uniqKey="Dudas G">G Dudas</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Dudas, G" uniqKey="Dudas G">G Dudas</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Fagbo, Sf" uniqKey="Fagbo S">SF Fagbo</name></author><author><name sortKey="Skakni, L" uniqKey="Skakni L">L Skakni</name></author><author><name sortKey="Chu, Dk" uniqKey="Chu D">DK Chu</name></author><author><name sortKey="Garbati, Ma" uniqKey="Garbati M">MA Garbati</name></author><author><name sortKey="Joseph, M" uniqKey="Joseph M">M Joseph</name></author><author><name sortKey="Peiris, M" uniqKey="Peiris M">M Peiris</name></author><author><name sortKey="Hakawi, Am" uniqKey="Hakawi A">AM Hakawi</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Faria, Nr" uniqKey="Faria N">NR Faria</name></author><author><name sortKey="Suchard, Ma" uniqKey="Suchard M">MA Suchard</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author><author><name sortKey="Streicker, Dg" uniqKey="Streicker D">DG Streicker</name></author><author><name sortKey="Lemey, P" uniqKey="Lemey P">P Lemey</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Frost, Sd" uniqKey="Frost S">SD Frost</name></author><author><name sortKey="Volz, Em" uniqKey="Volz E">EM Volz</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Gill, Ms" uniqKey="Gill M">MS Gill</name></author><author><name sortKey="Lemey, P" uniqKey="Lemey P">P Lemey</name></author><author><name sortKey="Faria, Nr" uniqKey="Faria N">NR Faria</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author><author><name sortKey="Shapiro, B" uniqKey="Shapiro B">B Shapiro</name></author><author><name sortKey="Suchard, Ma" uniqKey="Suchard M">MA Suchard</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Gire, Sk" uniqKey="Gire S">SK Gire</name></author><author><name sortKey="Goba, A" uniqKey="Goba A">A Goba</name></author><author><name sortKey="Andersen, Kg" uniqKey="Andersen K">KG Andersen</name></author><author><name sortKey="Sealfon, Rs" uniqKey="Sealfon R">RS Sealfon</name></author><author><name sortKey="Park, Dj" uniqKey="Park D">DJ Park</name></author><author><name sortKey="Kanneh, L" uniqKey="Kanneh L">L Kanneh</name></author><author><name sortKey="Jalloh, S" uniqKey="Jalloh S">S Jalloh</name></author><author><name sortKey="Momoh, M" uniqKey="Momoh M">M Momoh</name></author><author><name sortKey="Fullah, M" uniqKey="Fullah M">M Fullah</name></author><author><name sortKey="Dudas, G" uniqKey="Dudas G">G Dudas</name></author><author><name sortKey="Wohl, S" uniqKey="Wohl S">S Wohl</name></author><author><name sortKey="Moses, Lm" uniqKey="Moses L">LM Moses</name></author><author><name sortKey="Yozwiak, Nl" uniqKey="Yozwiak N">NL Yozwiak</name></author><author><name sortKey="Winnicki, S" uniqKey="Winnicki S">S Winnicki</name></author><author><name sortKey="Matranga, Cb" uniqKey="Matranga C">CB Matranga</name></author><author><name sortKey="Malboeuf, Cm" uniqKey="Malboeuf C">CM Malboeuf</name></author><author><name sortKey="Qu, J" uniqKey="Qu J">J Qu</name></author><author><name sortKey="Gladden, Ad" uniqKey="Gladden A">AD Gladden</name></author><author><name sortKey="Schaffner, Sf" uniqKey="Schaffner S">SF Schaffner</name></author><author><name sortKey="Yang, X" uniqKey="Yang X">X Yang</name></author><author><name sortKey="Jiang, Pp" uniqKey="Jiang P">PP Jiang</name></author><author><name sortKey="Nekoui, M" uniqKey="Nekoui M">M Nekoui</name></author><author><name sortKey="Colubri, A" uniqKey="Colubri A">A Colubri</name></author><author><name sortKey="Coomber, Mr" uniqKey="Coomber M">MR Coomber</name></author><author><name sortKey="Fonnie, M" uniqKey="Fonnie M">M Fonnie</name></author><author><name sortKey="Moigboi, A" uniqKey="Moigboi A">A Moigboi</name></author><author><name sortKey="Gbakie, M" uniqKey="Gbakie M">M Gbakie</name></author><author><name sortKey="Kamara, Fk" uniqKey="Kamara F">FK Kamara</name></author><author><name sortKey="Tucker, V" uniqKey="Tucker V">V Tucker</name></author><author><name sortKey="Konuwa, E" uniqKey="Konuwa E">E Konuwa</name></author><author><name sortKey="Saffa, S" uniqKey="Saffa S">S Saffa</name></author><author><name sortKey="Sellu, J" uniqKey="Sellu J">J Sellu</name></author><author><name sortKey="Jalloh, Aa" uniqKey="Jalloh A">AA Jalloh</name></author><author><name sortKey="Kovoma, A" uniqKey="Kovoma A">A Kovoma</name></author><author><name sortKey="Koninga, J" uniqKey="Koninga J">J Koninga</name></author><author><name sortKey="Mustapha, I" uniqKey="Mustapha I">I Mustapha</name></author><author><name sortKey="Kargbo, K" uniqKey="Kargbo K">K Kargbo</name></author><author><name sortKey="Foday, M" uniqKey="Foday M">M Foday</name></author><author><name sortKey="Yillah, M" uniqKey="Yillah M">M Yillah</name></author><author><name sortKey="Kanneh, F" uniqKey="Kanneh F">F Kanneh</name></author><author><name sortKey="Robert, W" uniqKey="Robert W">W Robert</name></author><author><name sortKey="Massally, Jl" uniqKey="Massally J">JL Massally</name></author><author><name sortKey="Chapman, Sb" uniqKey="Chapman S">SB Chapman</name></author><author><name sortKey="Bochicchio, J" uniqKey="Bochicchio J">J Bochicchio</name></author><author><name sortKey="Murphy, C" uniqKey="Murphy C">C Murphy</name></author><author><name sortKey="Nusbaum, C" uniqKey="Nusbaum C">C Nusbaum</name></author><author><name sortKey="Young, S" uniqKey="Young S">S Young</name></author><author><name sortKey="Birren, Bw" uniqKey="Birren B">BW Birren</name></author><author><name sortKey="Grant, Ds" uniqKey="Grant D">DS Grant</name></author><author><name sortKey="Scheiffelin, Js" uniqKey="Scheiffelin J">JS Scheiffelin</name></author><author><name sortKey="Lander, Es" uniqKey="Lander E">ES Lander</name></author><author><name sortKey="Happi, C" uniqKey="Happi C">C Happi</name></author><author><name sortKey="Gevao, Sm" uniqKey="Gevao S">SM Gevao</name></author><author><name sortKey="Gnirke, A" uniqKey="Gnirke A">A Gnirke</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author><author><name sortKey="Garry, Rf" uniqKey="Garry R">RF Garry</name></author><author><name sortKey="Khan, Sh" uniqKey="Khan S">SH Khan</name></author><author><name sortKey="Sabeti, Pc" uniqKey="Sabeti P">PC Sabeti</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Grubaugh, Nd" uniqKey="Grubaugh N">ND Grubaugh</name></author><author><name sortKey="Ladner, Jt" uniqKey="Ladner J">JT Ladner</name></author><author><name sortKey="Kraemer, Mug" uniqKey="Kraemer M">MUG Kraemer</name></author><author><name sortKey="Dudas, G" uniqKey="Dudas G">G Dudas</name></author><author><name sortKey="Tan, Al" uniqKey="Tan A">AL Tan</name></author><author><name sortKey="Gangavarapu, K" uniqKey="Gangavarapu K">K Gangavarapu</name></author><author><name sortKey="Wiley, Mr" uniqKey="Wiley M">MR Wiley</name></author><author><name sortKey="White, S" uniqKey="White S">S White</name></author><author><name sortKey="Theze, J" uniqKey="Theze J">J Thézé</name></author><author><name sortKey="Magnani, Dm" uniqKey="Magnani D">DM Magnani</name></author><author><name sortKey="Prieto, K" uniqKey="Prieto K">K Prieto</name></author><author><name sortKey="Reyes, D" uniqKey="Reyes D">D Reyes</name></author><author><name sortKey="Bingham, Am" uniqKey="Bingham A">AM Bingham</name></author><author><name sortKey="Paul, Lm" uniqKey="Paul L">LM Paul</name></author><author><name sortKey="Robles Sikisaka, R" uniqKey="Robles Sikisaka R">R Robles-Sikisaka</name></author><author><name sortKey="Oliveira, G" uniqKey="Oliveira G">G Oliveira</name></author><author><name sortKey="Pronty, D" uniqKey="Pronty D">D Pronty</name></author><author><name sortKey="Barcellona, Cm" uniqKey="Barcellona C">CM Barcellona</name></author><author><name sortKey="Metsky, Hc" uniqKey="Metsky H">HC Metsky</name></author><author><name sortKey="Baniecki, Ml" uniqKey="Baniecki M">ML Baniecki</name></author><author><name sortKey="Barnes, Kg" uniqKey="Barnes K">KG Barnes</name></author><author><name sortKey="Chak, B" uniqKey="Chak B">B Chak</name></author><author><name sortKey="Freije, Ca" uniqKey="Freije C">CA Freije</name></author><author><name sortKey="Gladden Young, A" uniqKey="Gladden Young A">A Gladden-Young</name></author><author><name sortKey="Gnirke, A" uniqKey="Gnirke A">A Gnirke</name></author><author><name sortKey="Luo, C" uniqKey="Luo C">C Luo</name></author><author><name sortKey="Macinnis, B" uniqKey="Macinnis B">B MacInnis</name></author><author><name sortKey="Matranga, Cb" uniqKey="Matranga C">CB Matranga</name></author><author><name sortKey="Park, Dj" uniqKey="Park D">DJ Park</name></author><author><name sortKey="Qu, J" uniqKey="Qu J">J Qu</name></author><author><name sortKey="Schaffner, Sf" uniqKey="Schaffner S">SF Schaffner</name></author><author><name sortKey="Tomkins Tinch, C" uniqKey="Tomkins Tinch C">C Tomkins-Tinch</name></author><author><name sortKey="West, Kl" uniqKey="West K">KL West</name></author><author><name sortKey="Winnicki, Sm" uniqKey="Winnicki S">SM Winnicki</name></author><author><name sortKey="Wohl, S" uniqKey="Wohl S">S Wohl</name></author><author><name sortKey="Yozwiak, Nl" uniqKey="Yozwiak N">NL Yozwiak</name></author><author><name sortKey="Quick, J" uniqKey="Quick J">J Quick</name></author><author><name sortKey="Fauver, Jr" uniqKey="Fauver J">JR Fauver</name></author><author><name sortKey="Khan, K" uniqKey="Khan K">K Khan</name></author><author><name sortKey="Brent, Se" uniqKey="Brent S">SE Brent</name></author><author><name sortKey="Reiner, Rc" uniqKey="Reiner R">RC Reiner</name></author><author><name sortKey="Lichtenberger, Pn" uniqKey="Lichtenberger P">PN Lichtenberger</name></author><author><name sortKey="Ricciardi, Mj" uniqKey="Ricciardi M">MJ Ricciardi</name></author><author><name sortKey="Bailey, Vk" uniqKey="Bailey V">VK Bailey</name></author><author><name sortKey="Watkins, Di" uniqKey="Watkins D">DI Watkins</name></author><author><name sortKey="Cone, Mr" uniqKey="Cone M">MR Cone</name></author><author><name sortKey="Kopp, Ew" uniqKey="Kopp E">EW Kopp</name></author><author><name sortKey="Hogan, Kn" uniqKey="Hogan K">KN Hogan</name></author><author><name sortKey="Cannons, Ac" uniqKey="Cannons A">AC Cannons</name></author><author><name sortKey="Jean, R" uniqKey="Jean R">R Jean</name></author><author><name sortKey="Monaghan, Aj" uniqKey="Monaghan A">AJ Monaghan</name></author><author><name sortKey="Garry, Rf" uniqKey="Garry R">RF Garry</name></author><author><name sortKey="Loman, Nj" uniqKey="Loman N">NJ Loman</name></author><author><name sortKey="Faria, Nr" uniqKey="Faria N">NR Faria</name></author><author><name sortKey="Porcelli, Mc" uniqKey="Porcelli M">MC Porcelli</name></author><author><name sortKey="Vasquez, C" uniqKey="Vasquez C">C Vasquez</name></author><author><name sortKey="Nagle, Er" uniqKey="Nagle E">ER Nagle</name></author><author><name sortKey="Cummings, Dat" uniqKey="Cummings D">DAT Cummings</name></author><author><name sortKey="Stanek, D" uniqKey="Stanek D">D Stanek</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author><author><name sortKey="Sanchez Lockhart, M" uniqKey="Sanchez Lockhart M">M Sanchez-Lockhart</name></author><author><name sortKey="Sabeti, Pc" uniqKey="Sabeti P">PC Sabeti</name></author><author><name sortKey="Gillis, Ld" uniqKey="Gillis L">LD Gillis</name></author><author><name sortKey="Michael, Sf" uniqKey="Michael S">SF Michael</name></author><author><name sortKey="Bedford, T" uniqKey="Bedford T">T Bedford</name></author><author><name sortKey="Pybus, Og" uniqKey="Pybus O">OG Pybus</name></author><author><name sortKey="Isern, S" uniqKey="Isern S">S Isern</name></author><author><name sortKey="Palacios, G" uniqKey="Palacios G">G Palacios</name></author><author><name sortKey="Andersen, Kg" uniqKey="Andersen K">KG Andersen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Guindon, S" uniqKey="Guindon S">S Guindon</name></author><author><name sortKey="Gascuel, O" uniqKey="Gascuel O">O Gascuel</name></author><author><name sortKey="A Simple, Rb" uniqKey="A Simple R">RB A Simple</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Haagmans, Bl" uniqKey="Haagmans B">BL Haagmans</name></author><author><name sortKey="Al Dhahiry, Sh" uniqKey="Al Dhahiry S">SH Al Dhahiry</name></author><author><name sortKey="Reusken, Cb" uniqKey="Reusken C">CB Reusken</name></author><author><name sortKey="Raj, Vs" uniqKey="Raj V">VS Raj</name></author><author><name sortKey="Galiano, M" uniqKey="Galiano M">M Galiano</name></author><author><name sortKey="Myers, R" uniqKey="Myers R">R Myers</name></author><author><name sortKey="Godeke, Gj" uniqKey="Godeke G">GJ Godeke</name></author><author><name sortKey="Jonges, M" uniqKey="Jonges M">M Jonges</name></author><author><name sortKey="Farag, E" uniqKey="Farag E">E Farag</name></author><author><name sortKey="Diab, A" uniqKey="Diab A">A Diab</name></author><author><name sortKey="Ghobashy, H" uniqKey="Ghobashy H">H Ghobashy</name></author><author><name sortKey="Alhajri, F" uniqKey="Alhajri F">F Alhajri</name></author><author><name sortKey="Al Thani, M" uniqKey="Al Thani M">M Al-Thani</name></author><author><name sortKey="Al Marri, Sa" uniqKey="Al Marri S">SA Al-Marri</name></author><author><name sortKey="Al Romaihi, He" uniqKey="Al Romaihi H">HE Al Romaihi</name></author><author><name sortKey="Al Khal, A" uniqKey="Al Khal A">A Al Khal</name></author><author><name sortKey="Bermingham, A" uniqKey="Bermingham A">A Bermingham</name></author><author><name sortKey="Osterhaus, Ad" uniqKey="Osterhaus A">AD Osterhaus</name></author><author><name sortKey="Alhajri, Mm" uniqKey="Alhajri M">MM AlHajri</name></author><author><name sortKey="Koopmans, Mp" uniqKey="Koopmans M">MP Koopmans</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hasegawa, M" uniqKey="Hasegawa M">M Hasegawa</name></author><author><name sortKey="Kishino, H" uniqKey="Kishino H">H Kishino</name></author><author><name sortKey="Yano, T" uniqKey="Yano T">T Yano</name></author><author><name sortKey="Ta, Y" uniqKey="Ta Y">Y Ta</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Heled, J" uniqKey="Heled J">J Heled</name></author><author><name sortKey="Bouckaert, Rr" uniqKey="Bouckaert R">RR Bouckaert</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hemida, Mg" uniqKey="Hemida M">MG Hemida</name></author><author><name sortKey="Chu, Dk" uniqKey="Chu D">DK Chu</name></author><author><name sortKey="Poon, Ll" uniqKey="Poon L">LL Poon</name></author><author><name sortKey="Perera, Ra" uniqKey="Perera R">RA Perera</name></author><author><name sortKey="Alhammadi, Ma" uniqKey="Alhammadi M">MA Alhammadi</name></author><author><name sortKey="Ng, Hy" uniqKey="Ng H">HY Ng</name></author><author><name sortKey="Siu, Ly" uniqKey="Siu L">LY Siu</name></author><author><name sortKey="Guan, Y" uniqKey="Guan Y">Y Guan</name></author><author><name sortKey="Alnaeem, A" uniqKey="Alnaeem A">A Alnaeem</name></author><author><name sortKey="Peiris, M" uniqKey="Peiris M">M Peiris</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Herrewegh, Aa" uniqKey="Herrewegh A">AA Herrewegh</name></author><author><name sortKey="Smeenk, I" uniqKey="Smeenk I">I Smeenk</name></author><author><name sortKey="Horzinek, Mc" uniqKey="Horzinek M">MC Horzinek</name></author><author><name sortKey="Rottier, Pj" uniqKey="Rottier P">PJ Rottier</name></author><author><name sortKey="De Groot, Rj" uniqKey="De Groot R">RJ de Groot</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hon, Cc" uniqKey="Hon C">CC Hon</name></author><author><name sortKey="Lam, Ty" uniqKey="Lam T">TY Lam</name></author><author><name sortKey="Shi, Zl" uniqKey="Shi Z">ZL Shi</name></author><author><name sortKey="Drummond, Aj" uniqKey="Drummond A">AJ Drummond</name></author><author><name sortKey="Yip, Cw" uniqKey="Yip C">CW Yip</name></author><author><name sortKey="Zeng, F" uniqKey="Zeng F">F Zeng</name></author><author><name sortKey="Lam, Py" uniqKey="Lam P">PY Lam</name></author><author><name sortKey="Leung, Fc" uniqKey="Leung F">FC Leung</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hunter, Jc" uniqKey="Hunter J">JC Hunter</name></author><author><name sortKey="Nguyen, D" uniqKey="Nguyen D">D Nguyen</name></author><author><name sortKey="Aden, B" uniqKey="Aden B">B Aden</name></author><author><name sortKey="Al Bandar, Z" uniqKey="Al Bandar Z">Z Al Bandar</name></author><author><name sortKey="Al Dhaheri, W" uniqKey="Al Dhaheri W">W Al Dhaheri</name></author><author><name sortKey="Abu Elkheir, K" uniqKey="Abu Elkheir K">K Abu Elkheir</name></author><author><name sortKey="Khudair, A" uniqKey="Khudair A">A Khudair</name></author><author><name sortKey="Al Mulla, M" uniqKey="Al Mulla M">M Al Mulla</name></author><author><name sortKey="El Saleh, F" uniqKey="El Saleh F">F El Saleh</name></author><author><name sortKey="Imambaccus, H" uniqKey="Imambaccus H">H Imambaccus</name></author><author><name sortKey="Al Kaabi, N" uniqKey="Al Kaabi N">N Al Kaabi</name></author><author><name sortKey="Sheikh, Fa" uniqKey="Sheikh F">FA Sheikh</name></author><author><name sortKey="Sasse, J" uniqKey="Sasse J">J Sasse</name></author><author><name sortKey="Turner, A" uniqKey="Turner A">A Turner</name></author><author><name sortKey="Abdel Wareth, L" uniqKey="Abdel Wareth L">L Abdel Wareth</name></author><author><name sortKey="Weber, S" uniqKey="Weber S">S Weber</name></author><author><name sortKey="Al Ameri, A" uniqKey="Al Ameri A">A Al Ameri</name></author><author><name sortKey="Abu Amer, W" uniqKey="Abu Amer W">W Abu Amer</name></author><author><name sortKey="Alami, Nn" uniqKey="Alami N">NN Alami</name></author><author><name sortKey="Bunga, S" uniqKey="Bunga S">S Bunga</name></author><author><name sortKey="Haynes, Lm" uniqKey="Haynes L">LM Haynes</name></author><author><name sortKey="Hall, Aj" uniqKey="Hall A">AJ Hall</name></author><author><name sortKey="Kallen, Aj" uniqKey="Kallen A">AJ Kallen</name></author><author><name sortKey="Kuhar, D" uniqKey="Kuhar D">D Kuhar</name></author><author><name sortKey="Pham, H" uniqKey="Pham H">H Pham</name></author><author><name sortKey="Pringle, K" uniqKey="Pringle K">K Pringle</name></author><author><name sortKey="Tong, S" uniqKey="Tong S">S Tong</name></author><author><name sortKey="Whitaker, Bl" uniqKey="Whitaker B">BL Whitaker</name></author><author><name sortKey="Gerber, Si" uniqKey="Gerber S">SI Gerber</name></author><author><name sortKey="Al Hosani, Fi" uniqKey="Al Hosani F">FI Al Hosani</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kandeil, A" uniqKey="Kandeil A">A Kandeil</name></author><author><name sortKey="Shehata, Mm" uniqKey="Shehata M">MM Shehata</name></author><author><name sortKey="El Shesheny, R" uniqKey="El Shesheny R">R El Shesheny</name></author><author><name sortKey="Gomaa, Mr" uniqKey="Gomaa M">MR Gomaa</name></author><author><name sortKey="Ali, Ma" uniqKey="Ali M">MA Ali</name></author><author><name sortKey="Kayali, G" uniqKey="Kayali G">G Kayali</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kapoor, M" uniqKey="Kapoor M">M Kapoor</name></author><author><name sortKey="Pringle, K" uniqKey="Pringle K">K Pringle</name></author><author><name sortKey="Kumar, A" uniqKey="Kumar A">A Kumar</name></author><author><name sortKey="Dearth, S" uniqKey="Dearth S">S Dearth</name></author><author><name sortKey="Liu, L" uniqKey="Liu L">L Liu</name></author><author><name sortKey="Lovchik, J" uniqKey="Lovchik J">J Lovchik</name></author><author><name sortKey="Perez, O" uniqKey="Perez O">O Perez</name></author><author><name sortKey="Pontones, P" uniqKey="Pontones P">P Pontones</name></author><author><name sortKey="Richards, S" uniqKey="Richards S">S Richards</name></author><author><name sortKey="Yeadon Fagbohun, J" uniqKey="Yeadon Fagbohun J">J Yeadon-Fagbohun</name></author><author><name sortKey="Breakwell, L" uniqKey="Breakwell L">L Breakwell</name></author><author><name sortKey="Chea, N" uniqKey="Chea N">N Chea</name></author><author><name sortKey="Cohen, Nj" uniqKey="Cohen N">NJ Cohen</name></author><author><name sortKey="Schneider, E" uniqKey="Schneider E">E Schneider</name></author><author><name sortKey="Erdman, D" uniqKey="Erdman D">D Erdman</name></author><author><name sortKey="Haynes, L" uniqKey="Haynes L">L Haynes</name></author><author><name sortKey="Pallansch, M" uniqKey="Pallansch M">M Pallansch</name></author><author><name sortKey="Tao, Y" uniqKey="Tao Y">Y Tao</name></author><author><name sortKey="Tong, S" uniqKey="Tong S">S Tong</name></author><author><name sortKey="Gerber, S" uniqKey="Gerber S">S Gerber</name></author><author><name sortKey="Swerdlow, D" uniqKey="Swerdlow D">D Swerdlow</name></author><author><name sortKey="Feikin, Dr" uniqKey="Feikin D">DR Feikin</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Katoh, K" uniqKey="Katoh K">K Katoh</name></author><author><name sortKey="Standley, Dm" uniqKey="Standley D">DM Standley</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Keck, Jg" uniqKey="Keck J">JG Keck</name></author><author><name sortKey="Matsushima, Gk" uniqKey="Matsushima G">GK Matsushima</name></author><author><name sortKey="Makino, S" uniqKey="Makino S">S Makino</name></author><author><name sortKey="Fleming, Jo" uniqKey="Fleming J">JO Fleming</name></author><author><name sortKey="Vannier, Dm" uniqKey="Vannier D">DM Vannier</name></author><author><name sortKey="Stohlman, Sa" uniqKey="Stohlman S">SA Stohlman</name></author><author><name sortKey="Lai, Mm" uniqKey="Lai M">MM Lai</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kim, Y" uniqKey="Kim Y">Y Kim</name></author><author><name sortKey="Cheon, S" uniqKey="Cheon S">S Cheon</name></author><author><name sortKey="Min, Ck" uniqKey="Min C">CK Min</name></author><author><name sortKey="Sohn, Km" uniqKey="Sohn K">KM Sohn</name></author><author><name sortKey="Kang, Yj" uniqKey="Kang Y">YJ Kang</name></author><author><name sortKey="Cha, Yj" uniqKey="Cha Y">YJ Cha</name></author><author><name sortKey="Kang, Ji" uniqKey="Kang J">JI Kang</name></author><author><name sortKey="Han, Sk" uniqKey="Han S">SK Han</name></author><author><name sortKey="Ha, Ny" uniqKey="Ha N">NY Ha</name></author><author><name sortKey="Kim, G" uniqKey="Kim G">G Kim</name></author><author><name sortKey="Aigerim, A" uniqKey="Aigerim A">A Aigerim</name></author><author><name sortKey="Shin, Hm" uniqKey="Shin H">HM Shin</name></author><author><name sortKey="Choi, Ms" uniqKey="Choi M">MS Choi</name></author><author><name sortKey="Kim, S" uniqKey="Kim S">S Kim</name></author><author><name sortKey="Cho, Hs" uniqKey="Cho H">HS Cho</name></author><author><name sortKey="Kim, Ys" uniqKey="Kim Y">YS Kim</name></author><author><name sortKey="Cho, Nh" uniqKey="Cho N">NH Cho</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kim, Yj" uniqKey="Kim Y">YJ Kim</name></author><author><name sortKey="Cho, Yj" uniqKey="Cho Y">YJ Cho</name></author><author><name sortKey="Kim, Dw" uniqKey="Kim D">DW Kim</name></author><author><name sortKey="Yang, Js" uniqKey="Yang J">JS Yang</name></author><author><name sortKey="Kim, H" uniqKey="Kim H">H Kim</name></author><author><name sortKey="Park, S" uniqKey="Park S">S Park</name></author><author><name sortKey="Han, Yw" uniqKey="Han Y">YW Han</name></author><author><name sortKey="Yun, Mr" uniqKey="Yun M">MR Yun</name></author><author><name sortKey="Lee, Hs" uniqKey="Lee H">HS Lee</name></author><author><name sortKey="Kim, Ar" uniqKey="Kim A">AR Kim</name></author><author><name sortKey="Heo, Dr" uniqKey="Heo D">DR Heo</name></author><author><name sortKey="Kim, Ja" uniqKey="Kim J">JA Kim</name></author><author><name sortKey="Kim, Sj" uniqKey="Kim S">SJ Kim</name></author><author><name sortKey="Jung, Hd" uniqKey="Jung H">HD Jung</name></author><author><name sortKey="Kim, N" uniqKey="Kim N">N Kim</name></author><author><name sortKey="Yoon, Sh" uniqKey="Yoon S">SH Yoon</name></author><author><name sortKey="Nam, Jg" uniqKey="Nam J">JG Nam</name></author><author><name sortKey="Kang, Hj" uniqKey="Kang H">HJ Kang</name></author><author><name sortKey="Cheong, Hm" uniqKey="Cheong H">HM Cheong</name></author><author><name sortKey="Lee, Js" uniqKey="Lee J">JS Lee</name></author><author><name sortKey="Chun, J" uniqKey="Chun J">J Chun</name></author><author><name sortKey="Kim, Ss" uniqKey="Kim S">SS Kim</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kosakovsky Pond, Sl" uniqKey="Kosakovsky Pond S">SL Kosakovsky Pond</name></author><author><name sortKey="Posada, D" uniqKey="Posada D">D Posada</name></author><author><name sortKey="Gravenor, Mb" uniqKey="Gravenor M">MB Gravenor</name></author><author><name sortKey="Woelk, Ch" uniqKey="Woelk C">CH Woelk</name></author><author><name sortKey="Frost, Sd" uniqKey="Frost S">SD Frost</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kottier, Sa" uniqKey="Kottier S">SA Kottier</name></author><author><name sortKey="Cavanagh, D" uniqKey="Cavanagh D">D Cavanagh</name></author><author><name sortKey="Britton, P" uniqKey="Britton P">P Britton</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kuhnert, D" uniqKey="Kuhnert D">D Kühnert</name></author><author><name sortKey="Stadler, T" uniqKey="Stadler T">T Stadler</name></author><author><name sortKey="Vaughan, Tg" uniqKey="Vaughan T">TG Vaughan</name></author><author><name sortKey="Drummond, Aj" uniqKey="Drummond A">AJ Drummond</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lai, Mm" uniqKey="Lai M">MM Lai</name></author><author><name sortKey="Baric, Rs" uniqKey="Baric R">RS Baric</name></author><author><name sortKey="Makino, S" uniqKey="Makino S">S Makino</name></author><author><name sortKey="Keck, Jg" uniqKey="Keck J">JG Keck</name></author><author><name sortKey="Egbert, J" uniqKey="Egbert J">J Egbert</name></author><author><name sortKey="Leibowitz, Jl" uniqKey="Leibowitz J">JL Leibowitz</name></author><author><name sortKey="Stohlman, Sa" uniqKey="Stohlman S">SA Stohlman</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lamers, Mm" uniqKey="Lamers M">MM Lamers</name></author><author><name sortKey="Raj, Vs" uniqKey="Raj V">VS Raj</name></author><author><name sortKey="Shafei, M" uniqKey="Shafei M">M Shafei</name></author><author><name sortKey="Ali, Ss" uniqKey="Ali S">SS Ali</name></author><author><name sortKey="Abdallh, Sm" uniqKey="Abdallh S">SM Abdallh</name></author><author><name sortKey="Gazo, M" uniqKey="Gazo M">M Gazo</name></author><author><name sortKey="Nofal, S" uniqKey="Nofal S">S Nofal</name></author><author><name sortKey="Lu, X" uniqKey="Lu X">X Lu</name></author><author><name sortKey="Erdman, Dd" uniqKey="Erdman D">DD Erdman</name></author><author><name sortKey="Koopmans, Mp" uniqKey="Koopmans M">MP Koopmans</name></author><author><name sortKey="Abdallat, M" uniqKey="Abdallat M">M Abdallat</name></author><author><name sortKey="Haddadin, A" uniqKey="Haddadin A">A Haddadin</name></author><author><name sortKey="Haagmans, Bl" uniqKey="Haagmans B">BL Haagmans</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lau, Sk" uniqKey="Lau S">SK Lau</name></author><author><name sortKey="Wernery, R" uniqKey="Wernery R">R Wernery</name></author><author><name sortKey="Wong, Ey" uniqKey="Wong E">EY Wong</name></author><author><name sortKey="Joseph, S" uniqKey="Joseph S">S Joseph</name></author><author><name sortKey="Tsang, Ak" uniqKey="Tsang A">AK Tsang</name></author><author><name sortKey="Patteril, Na" uniqKey="Patteril N">NA Patteril</name></author><author><name sortKey="Elizabeth, Sk" uniqKey="Elizabeth S">SK Elizabeth</name></author><author><name sortKey="Chan, Kh" uniqKey="Chan K">KH Chan</name></author><author><name sortKey="Muhammed, R" uniqKey="Muhammed R">R Muhammed</name></author><author><name sortKey="Kinne, J" uniqKey="Kinne J">J Kinne</name></author><author><name sortKey="Yuen, Ky" uniqKey="Yuen K">KY Yuen</name></author><author><name sortKey="Wernery, U" uniqKey="Wernery U">U Wernery</name></author><author><name sortKey="Woo, Pc" uniqKey="Woo P">PC Woo</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lemey, P" uniqKey="Lemey P">P Lemey</name></author><author><name sortKey="Rambaut, A" uniqKey="Rambaut A">A Rambaut</name></author><author><name sortKey="Drummond, Aj" uniqKey="Drummond A">AJ Drummond</name></author><author><name sortKey="Suchard, Ma" uniqKey="Suchard M">MA Suchard</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lipsitch, M" uniqKey="Lipsitch M">M Lipsitch</name></author><author><name sortKey="Barclay, W" uniqKey="Barclay W">W Barclay</name></author><author><name sortKey="Raman, R" uniqKey="Raman R">R Raman</name></author><author><name sortKey="Russell, Cj" uniqKey="Russell C">CJ Russell</name></author><author><name sortKey="Belser, Ja" uniqKey="Belser J">JA Belser</name></author><author><name sortKey="Cobey, S" uniqKey="Cobey S">S Cobey</name></author><author><name sortKey="Kasson, Pm" uniqKey="Kasson P">PM Kasson</name></author><author><name sortKey="Lloyd Smith, Jo" uniqKey="Lloyd Smith J">JO Lloyd-Smith</name></author><author><name sortKey="Maurer Stroh, S" uniqKey="Maurer Stroh S">S Maurer-Stroh</name></author><author><name sortKey="Riley, S" uniqKey="Riley S">S Riley</name></author><author><name sortKey="Beauchemin, Ca" uniqKey="Beauchemin C">CA Beauchemin</name></author><author><name sortKey="Bedford, T" uniqKey="Bedford T">T Bedford</name></author><author><name sortKey="Friedrich, Tc" uniqKey="Friedrich T">TC Friedrich</name></author><author><name sortKey="Handel, A" uniqKey="Handel A">A Handel</name></author><author><name sortKey="Herfst, S" uniqKey="Herfst S">S Herfst</name></author><author><name sortKey="Murcia, Pr" uniqKey="Murcia P">PR Murcia</name></author><author><name sortKey="Roche, B" uniqKey="Roche B">B Roche</name></author><author><name sortKey="Wilke, Co" uniqKey="Wilke C">CO Wilke</name></author><author><name sortKey="Russell, Ca" uniqKey="Russell C">CA Russell</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Liu, D" uniqKey="Liu D">D Liu</name></author><author><name sortKey="Shi, W" uniqKey="Shi W">W Shi</name></author><author><name sortKey="Shi, Y" uniqKey="Shi Y">Y Shi</name></author><author><name sortKey="Wang, D" uniqKey="Wang D">D Wang</name></author><author><name sortKey="Xiao, H" uniqKey="Xiao H">H Xiao</name></author><author><name sortKey="Li, W" uniqKey="Li W">W Li</name></author><author><name sortKey="Bi, Y" uniqKey="Bi Y">Y Bi</name></author><author><name sortKey="Wu, Y" uniqKey="Wu Y">Y Wu</name></author><author><name sortKey="Li, X" uniqKey="Li X">X Li</name></author><author><name sortKey="Yan, J" uniqKey="Yan J">J Yan</name></author><author><name sortKey="Liu, W" uniqKey="Liu W">W Liu</name></author><author><name sortKey="Zhao, G" uniqKey="Zhao G">G Zhao</name></author><author><name sortKey="Yang, W" uniqKey="Yang W">W Yang</name></author><author><name sortKey="Wang, Y" uniqKey="Wang Y">Y Wang</name></author><author><name sortKey="Ma, J" uniqKey="Ma J">J Ma</name></author><author><name sortKey="Shu, Y" uniqKey="Shu Y">Y Shu</name></author><author><name sortKey="Lei, F" uniqKey="Lei F">F Lei</name></author><author><name sortKey="Gao, Gf" uniqKey="Gao G">GF Gao</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lloyd Smith, Jo" uniqKey="Lloyd Smith J">JO Lloyd-Smith</name></author><author><name sortKey="Schreiber, Sj" uniqKey="Schreiber S">SJ Schreiber</name></author><author><name sortKey="Kopp, Pe" uniqKey="Kopp P">PE Kopp</name></author><author><name sortKey="Getz, Wm" uniqKey="Getz W">WM Getz</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lu, X" uniqKey="Lu X">X Lu</name></author><author><name sortKey="Rowe, La" uniqKey="Rowe L">LA Rowe</name></author><author><name sortKey="Frace, M" uniqKey="Frace M">M Frace</name></author><author><name sortKey="Stevens, J" uniqKey="Stevens J">J Stevens</name></author><author><name sortKey="Abedi, Gr" uniqKey="Abedi G">GR Abedi</name></author><author><name sortKey="Elnile, O" uniqKey="Elnile O">O Elnile</name></author><author><name sortKey="Banassir, T" uniqKey="Banassir T">T Banassir</name></author><author><name sortKey="Al Masri, M" uniqKey="Al Masri M">M Al-Masri</name></author><author><name sortKey="Watson, Jt" uniqKey="Watson J">JT Watson</name></author><author><name sortKey="Assiri, A" uniqKey="Assiri A">A Assiri</name></author><author><name sortKey="Erdman, Dd" uniqKey="Erdman D">DD Erdman</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lycett, S" uniqKey="Lycett S">S Lycett</name></author><author><name sortKey="Bodewes, R" uniqKey="Bodewes R">R Bodewes</name></author><author><name sortKey="Pohlmann, A" uniqKey="Pohlmann A">A Pohlmann</name></author><author><name sortKey="Banks, J" uniqKey="Banks J">J Banks</name></author><author><name sortKey="Banyai, K" uniqKey="Banyai K">K Banyai</name></author><author><name sortKey="Boni, M" uniqKey="Boni M">M Boni</name></author><author><name sortKey="Bouwstra, R" uniqKey="Bouwstra R">R Bouwstra</name></author><author><name sortKey="Breed, A" uniqKey="Breed A">A Breed</name></author><author><name sortKey="Brown, I" uniqKey="Brown I">I Brown</name></author><author><name sortKey="Chen, H" uniqKey="Chen H">H Chen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Makino, S" uniqKey="Makino S">S Makino</name></author><author><name sortKey="Keck, Jg" uniqKey="Keck J">JG Keck</name></author><author><name sortKey="Stohlman, Sa" uniqKey="Stohlman S">SA Stohlman</name></author><author><name sortKey="Lai, Mm" uniqKey="Lai M">MM Lai</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Martinez, Vp" uniqKey="Martinez V">VP Martinez</name></author><author><name sortKey="Bellomo, C" uniqKey="Bellomo C">C Bellomo</name></author><author><name sortKey="San Juan, J" uniqKey="San Juan J">J San Juan</name></author><author><name sortKey="Pinna, D" uniqKey="Pinna D">D Pinna</name></author><author><name sortKey="Forlenza, R" uniqKey="Forlenza R">R Forlenza</name></author><author><name sortKey="Elder, M" uniqKey="Elder M">M Elder</name></author><author><name sortKey="Padula, Pj" uniqKey="Padula P">PJ Padula</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Martinez Bakker, M" uniqKey="Martinez Bakker M">M Martinez-Bakker</name></author><author><name sortKey="Bakker, Km" uniqKey="Bakker K">KM Bakker</name></author><author><name sortKey="King, Aa" uniqKey="King A">AA King</name></author><author><name sortKey="Rohani, P" uniqKey="Rohani P">P Rohani</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Memish, Za" uniqKey="Memish Z">ZA Memish</name></author><author><name sortKey="Cotten, M" uniqKey="Cotten M">M Cotten</name></author><author><name sortKey="Meyer, B" uniqKey="Meyer B">B Meyer</name></author><author><name sortKey="Watson, Sj" uniqKey="Watson S">SJ Watson</name></author><author><name sortKey="Alsahafi, Aj" uniqKey="Alsahafi A">AJ Alsahafi</name></author><author><name sortKey="Al Rabeeah, Aa" uniqKey="Al Rabeeah A">AA Al Rabeeah</name></author><author><name sortKey="Corman, Vm" uniqKey="Corman V">VM Corman</name></author><author><name sortKey="Sieberg, A" uniqKey="Sieberg A">A Sieberg</name></author><author><name sortKey="Makhdoom, Hq" uniqKey="Makhdoom H">HQ Makhdoom</name></author><author><name sortKey="Assiri, A" uniqKey="Assiri A">A Assiri</name></author><author><name sortKey="Al Masri, M" uniqKey="Al Masri M">M Al Masri</name></author><author><name sortKey="Aldabbagh, S" uniqKey="Aldabbagh S">S Aldabbagh</name></author><author><name sortKey="Bosch, Bj" uniqKey="Bosch B">BJ Bosch</name></author><author><name sortKey="Beer, M" uniqKey="Beer M">M Beer</name></author><author><name sortKey="Muller, Ma" uniqKey="Muller M">MA Müller</name></author><author><name sortKey="Kellam, P" uniqKey="Kellam P">P Kellam</name></author><author><name sortKey="Drosten, C" uniqKey="Drosten C">C Drosten</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Mueller, Nf" uniqKey="Mueller N">NF Mueller</name></author><author><name sortKey="Rasmussen, Da" uniqKey="Rasmussen D">DA Rasmussen</name></author><author><name sortKey="Stadler, T" uniqKey="Stadler T">T Stadler</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Muller, Ma" uniqKey="Muller M">MA Müller</name></author><author><name sortKey="Corman, Vm" uniqKey="Corman V">VM Corman</name></author><author><name sortKey="Jores, J" uniqKey="Jores J">J Jores</name></author><author><name sortKey="Meyer, B" uniqKey="Meyer B">B Meyer</name></author><author><name sortKey="Younan, M" uniqKey="Younan M">M Younan</name></author><author><name sortKey="Liljander, A" uniqKey="Liljander A">A Liljander</name></author><author><name sortKey="Bosch, Bj" uniqKey="Bosch B">BJ Bosch</name></author><author><name sortKey="Lattwein, E" uniqKey="Lattwein E">E Lattwein</name></author><author><name sortKey="Hilali, M" uniqKey="Hilali M">M Hilali</name></author><author><name sortKey="Musa, Be" uniqKey="Musa B">BE Musa</name></author><author><name sortKey="Bornstein, S" uniqKey="Bornstein S">S Bornstein</name></author><author><name sortKey="Drosten, C" uniqKey="Drosten C">C Drosten</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Muller, Ma" uniqKey="Muller M">MA Müller</name></author><author><name sortKey="Meyer, B" uniqKey="Meyer B">B Meyer</name></author><author><name sortKey="Corman, Vm" uniqKey="Corman V">VM Corman</name></author><author><name sortKey="Al Masri, M" uniqKey="Al Masri M">M Al-Masri</name></author><author><name sortKey="Turkestani, A" uniqKey="Turkestani A">A Turkestani</name></author><author><name sortKey="Ritz, D" uniqKey="Ritz D">D Ritz</name></author><author><name sortKey="Sieberg, A" uniqKey="Sieberg A">A Sieberg</name></author><author><name sortKey="Aldabbagh, S" uniqKey="Aldabbagh S">S Aldabbagh</name></author><author><name sortKey="Bosch, Bj" uniqKey="Bosch B">BJ Bosch</name></author><author><name sortKey="Lattwein, E" uniqKey="Lattwein E">E Lattwein</name></author><author><name sortKey="Alhakeem, Rf" uniqKey="Alhakeem R">RF Alhakeem</name></author><author><name sortKey="Assiri, Am" uniqKey="Assiri A">AM Assiri</name></author><author><name sortKey="Albarrak, Am" uniqKey="Albarrak A">AM Albarrak</name></author><author><name sortKey="Al Shangiti, Am" uniqKey="Al Shangiti A">AM Al-Shangiti</name></author><author><name sortKey="Al Tawfiq, Ja" uniqKey="Al Tawfiq J">JA Al-Tawfiq</name></author><author><name sortKey="Wikramaratna, P" uniqKey="Wikramaratna P">P Wikramaratna</name></author><author><name sortKey="Alrabeeah, Aa" uniqKey="Alrabeeah A">AA Alrabeeah</name></author><author><name sortKey="Drosten, C" uniqKey="Drosten C">C Drosten</name></author><author><name sortKey="Memish, Za" uniqKey="Memish Z">ZA Memish</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Notohara, M" uniqKey="Notohara M">M Notohara</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Park, D" uniqKey="Park D">D Park</name></author><author><name sortKey="Huh, Hj" uniqKey="Huh H">HJ Huh</name></author><author><name sortKey="Kim, Yj" uniqKey="Kim Y">YJ Kim</name></author><author><name sortKey="Son, D S" uniqKey="Son D">D-S Son</name></author><author><name sortKey="Jeon, H J" uniqKey="Jeon H">H-J Jeon</name></author><author><name sortKey="Im, E H" uniqKey="Im E">E-H Im</name></author><author><name sortKey="Kim, J W" uniqKey="Kim J">J-W Kim</name></author><author><name sortKey="Lee, Ny" uniqKey="Lee N">NY Lee</name></author><author><name sortKey="Kang, E S" uniqKey="Kang E">E-S Kang</name></author><author><name sortKey="Kang, Ci" uniqKey="Kang C">CI Kang</name></author><author><name sortKey="Chung, Dr" uniqKey="Chung D">DR Chung</name></author><author><name sortKey="Ahn, J H" uniqKey="Ahn J">J-H Ahn</name></author><author><name sortKey="Peck, Kr" uniqKey="Peck K">KR Peck</name></author><author><name sortKey="Choi, Ss" uniqKey="Choi S">SS Choi</name></author><author><name sortKey="Kim, Y J" uniqKey="Kim Y">Y-J Kim</name></author><author><name sortKey="Ki, C S" uniqKey="Ki C">C-S Ki</name></author><author><name sortKey="Park, W Y" uniqKey="Park W">W-Y Park</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Park, M" uniqKey="Park M">M Park</name></author><author><name sortKey="Loverdo, C" uniqKey="Loverdo C">C Loverdo</name></author><author><name sortKey="Schreiber, Sj" uniqKey="Schreiber S">SJ Schreiber</name></author><author><name sortKey="Lloyd Smith, Jo" uniqKey="Lloyd Smith J">JO Lloyd-Smith</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Park, Wb" uniqKey="Park W">WB Park</name></author><author><name sortKey="Kwon, Nj" uniqKey="Kwon N">NJ Kwon</name></author><author><name sortKey="Choe, Pg" uniqKey="Choe P">PG Choe</name></author><author><name sortKey="Choi, Sj" uniqKey="Choi S">SJ Choi</name></author><author><name sortKey="Oh, Hs" uniqKey="Oh H">HS Oh</name></author><author><name sortKey="Lee, Sm" uniqKey="Lee S">SM Lee</name></author><author><name sortKey="Chong, H" uniqKey="Chong H">H Chong</name></author><author><name sortKey="Kim, Ji" uniqKey="Kim J">JI Kim</name></author><author><name sortKey="Song, Kh" uniqKey="Song K">KH Song</name></author><author><name sortKey="Bang, Jh" uniqKey="Bang J">JH Bang</name></author><author><name sortKey="Kim, Es" uniqKey="Kim E">ES Kim</name></author><author><name sortKey="Kim, Hb" uniqKey="Kim H">HB Kim</name></author><author><name sortKey="Park, Sw" uniqKey="Park S">SW Park</name></author><author><name sortKey="Kim, Nj" uniqKey="Kim N">NJ Kim</name></author><author><name sortKey="Oh, Md" uniqKey="Oh M">MD Oh</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Plipat, T" uniqKey="Plipat T">T Plipat</name></author><author><name sortKey="Buathong, R" uniqKey="Buathong R">R Buathong</name></author><author><name sortKey="Wacharapluesadee, S" uniqKey="Wacharapluesadee S">S Wacharapluesadee</name></author><author><name sortKey="Siriarayapon, P" uniqKey="Siriarayapon P">P Siriarayapon</name></author><author><name sortKey="Pittayawonganon, C" uniqKey="Pittayawonganon C">C Pittayawonganon</name></author><author><name sortKey="Sangsajja, C" uniqKey="Sangsajja C">C Sangsajja</name></author><author><name sortKey="Kaewpom, T" uniqKey="Kaewpom T">T Kaewpom</name></author><author><name sortKey="Petcharat, S" uniqKey="Petcharat S">S Petcharat</name></author><author><name sortKey="Ponpinit, T" uniqKey="Ponpinit T">T Ponpinit</name></author><author><name sortKey="Jumpasri, J" uniqKey="Jumpasri J">J Jumpasri</name></author><author><name sortKey="Joyjinda, Y" uniqKey="Joyjinda Y">Y Joyjinda</name></author><author><name sortKey="Rodpan, A" uniqKey="Rodpan A">A Rodpan</name></author><author><name sortKey="Ghai, S" uniqKey="Ghai S">S Ghai</name></author><author><name sortKey="Jittmittraphap, A" uniqKey="Jittmittraphap A">A Jittmittraphap</name></author><author><name sortKey="Khongwichit, S" uniqKey="Khongwichit S">S Khongwichit</name></author><author><name sortKey="Smith, Dr" uniqKey="Smith D">DR Smith</name></author><author><name sortKey="Corman, Vm" uniqKey="Corman V">VM Corman</name></author><author><name sortKey="Drosten, C" uniqKey="Drosten C">C Drosten</name></author><author><name sortKey="Hemachudha, T" uniqKey="Hemachudha T">T Hemachudha</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Quick, J" uniqKey="Quick J">J Quick</name></author><author><name sortKey="Ashton, P" uniqKey="Ashton P">P Ashton</name></author><author><name sortKey="Calus, S" uniqKey="Calus S">S Calus</name></author><author><name sortKey="Chatt, C" uniqKey="Chatt C">C Chatt</name></author><author><name sortKey="Gossain, S" uniqKey="Gossain S">S Gossain</name></author><author><name sortKey="Hawker, J" uniqKey="Hawker J">J Hawker</name></author><author><name sortKey="Nair, S" uniqKey="Nair S">S Nair</name></author><author><name sortKey="Neal, K" uniqKey="Neal K">K Neal</name></author><author><name sortKey="Nye, K" uniqKey="Nye K">K Nye</name></author><author><name sortKey="Peters, T" uniqKey="Peters T">T Peters</name></author><author><name sortKey="De Pinna, E" uniqKey="De Pinna E">E De Pinna</name></author><author><name sortKey="Robinson, E" uniqKey="Robinson E">E Robinson</name></author><author><name sortKey="Struthers, K" uniqKey="Struthers K">K Struthers</name></author><author><name sortKey="Webber, M" uniqKey="Webber M">M Webber</name></author><author><name sortKey="Catto, A" uniqKey="Catto A">A Catto</name></author><author><name sortKey="Dallman, Tj" uniqKey="Dallman T">TJ Dallman</name></author><author><name sortKey="Hawkey, P" uniqKey="Hawkey P">P Hawkey</name></author><author><name sortKey="Loman, Nj" uniqKey="Loman N">NJ Loman</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Raj, Vs" uniqKey="Raj V">VS Raj</name></author><author><name sortKey="Farag, Ea" uniqKey="Farag E">EA Farag</name></author><author><name sortKey="Reusken, Cb" uniqKey="Reusken C">CB Reusken</name></author><author><name sortKey="Lamers, Mm" uniqKey="Lamers M">MM Lamers</name></author><author><name sortKey="Pas, Sd" uniqKey="Pas S">SD Pas</name></author><author><name sortKey="Voermans, J" uniqKey="Voermans J">J Voermans</name></author><author><name sortKey="Smits, Sl" uniqKey="Smits S">SL Smits</name></author><author><name sortKey="Osterhaus, Ad" uniqKey="Osterhaus A">AD Osterhaus</name></author><author><name sortKey="Al Mawlawi, N" uniqKey="Al Mawlawi N">N Al-Mawlawi</name></author><author><name sortKey="Al Romaihi, He" uniqKey="Al Romaihi H">HE Al-Romaihi</name></author><author><name sortKey="Alhajri, Mm" uniqKey="Alhajri M">MM AlHajri</name></author><author><name sortKey="El Sayed, Am" uniqKey="El Sayed A">AM El-Sayed</name></author><author><name sortKey="Mohran, Ka" uniqKey="Mohran K">KA Mohran</name></author><author><name sortKey="Ghobashy, H" uniqKey="Ghobashy H">H Ghobashy</name></author><author><name sortKey="Alhajri, F" uniqKey="Alhajri F">F Alhajri</name></author><author><name sortKey="Al Thani, M" uniqKey="Al Thani M">M Al-Thani</name></author><author><name sortKey="Al Marri, Sa" uniqKey="Al Marri S">SA Al-Marri</name></author><author><name sortKey="El Maghraby, Mm" uniqKey="El Maghraby M">MM El-Maghraby</name></author><author><name sortKey="Koopmans, Mp" uniqKey="Koopmans M">MP Koopmans</name></author><author><name sortKey="Haagmans, Bl" uniqKey="Haagmans B">BL Haagmans</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Rasmussen, Da" uniqKey="Rasmussen D">DA Rasmussen</name></author><author><name sortKey="Volz, Em" uniqKey="Volz E">EM Volz</name></author><author><name sortKey="Koelle, K" uniqKey="Koelle K">K Koelle</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Reed, Kd" uniqKey="Reed K">KD Reed</name></author><author><name sortKey="Melski, Jw" uniqKey="Melski J">JW Melski</name></author><author><name sortKey="Graham, Mb" uniqKey="Graham M">MB Graham</name></author><author><name sortKey="Regnery, Rl" uniqKey="Regnery R">RL Regnery</name></author><author><name sortKey="Sotir, Mj" uniqKey="Sotir M">MJ Sotir</name></author><author><name sortKey="Wegner, Mv" uniqKey="Wegner M">MV Wegner</name></author><author><name sortKey="Kazmierczak, Jj" uniqKey="Kazmierczak J">JJ Kazmierczak</name></author><author><name sortKey="Stratman, Ej" uniqKey="Stratman E">EJ Stratman</name></author><author><name sortKey="Li, Y" uniqKey="Li Y">Y Li</name></author><author><name sortKey="Fairley, Ja" uniqKey="Fairley J">JA Fairley</name></author><author><name sortKey="Swain, Gr" uniqKey="Swain G">GR Swain</name></author><author><name sortKey="Olson, Va" uniqKey="Olson V">VA Olson</name></author><author><name sortKey="Sargent, Ek" uniqKey="Sargent E">EK Sargent</name></author><author><name sortKey="Kehl, Sc" uniqKey="Kehl S">SC Kehl</name></author><author><name sortKey="Frace, Ma" uniqKey="Frace M">MA Frace</name></author><author><name sortKey="Kline, R" uniqKey="Kline R">R Kline</name></author><author><name sortKey="Foldy, Sl" uniqKey="Foldy S">SL Foldy</name></author><author><name sortKey="Davis, Jp" uniqKey="Davis J">JP Davis</name></author><author><name sortKey="Damon, Ik" uniqKey="Damon I">IK Damon</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Reusken, Cb" uniqKey="Reusken C">CB Reusken</name></author><author><name sortKey="Farag, Ea" uniqKey="Farag E">EA Farag</name></author><author><name sortKey="Haagmans, Bl" uniqKey="Haagmans B">BL Haagmans</name></author><author><name sortKey="Mohran, Ka" uniqKey="Mohran K">KA Mohran</name></author><author><name sortKey="Godeke, Gj" uniqKey="Godeke G">GJ Godeke</name></author><author><name sortKey="Raj, S" uniqKey="Raj S">S Raj</name></author><author><name sortKey="Alhajri, F" uniqKey="Alhajri F">F Alhajri</name></author><author><name sortKey="Al Marri, Sa" uniqKey="Al Marri S">SA Al-Marri</name></author><author><name sortKey="Al Romaihi, He" uniqKey="Al Romaihi H">HE Al-Romaihi</name></author><author><name sortKey="Al Thani, M" uniqKey="Al Thani M">M Al-Thani</name></author><author><name sortKey="Bosch, Bj" uniqKey="Bosch B">BJ Bosch</name></author><author><name sortKey="Van Der Eijk, Aa" uniqKey="Van Der Eijk A">AA van der Eijk</name></author><author><name sortKey="El Sayed, Am" uniqKey="El Sayed A">AM El-Sayed</name></author><author><name sortKey="Ibrahim, Ak" uniqKey="Ibrahim A">AK Ibrahim</name></author><author><name sortKey="Al Molawi, N" uniqKey="Al Molawi N">N Al-Molawi</name></author><author><name sortKey="Muller, Ma" uniqKey="Muller M">MA Müller</name></author><author><name sortKey="Pasha, Sk" uniqKey="Pasha S">SK Pasha</name></author><author><name sortKey="Drosten, C" uniqKey="Drosten C">C Drosten</name></author><author><name sortKey="Alhajri, Mm" uniqKey="Alhajri M">MM AlHajri</name></author><author><name sortKey="Koopmans, Mp" uniqKey="Koopmans M">MP Koopmans</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Reusken, Cb" uniqKey="Reusken C">CB Reusken</name></author><author><name sortKey="Haagmans, Bl" uniqKey="Haagmans B">BL Haagmans</name></author><author><name sortKey="Muller, Ma" uniqKey="Muller M">MA Müller</name></author><author><name sortKey="Gutierrez, C" uniqKey="Gutierrez C">C Gutierrez</name></author><author><name sortKey="Godeke, Gj" uniqKey="Godeke G">GJ Godeke</name></author><author><name sortKey="Meyer, B" uniqKey="Meyer B">B Meyer</name></author><author><name sortKey="Muth, D" uniqKey="Muth D">D Muth</name></author><author><name sortKey="Raj, Vs" uniqKey="Raj V">VS Raj</name></author><author><name sortKey="Smits De Vries, L" uniqKey="Smits De Vries L">L Smits-De Vries</name></author><author><name sortKey="Corman, Vm" uniqKey="Corman V">VM Corman</name></author><author><name sortKey="Drexler, Jf" uniqKey="Drexler J">JF Drexler</name></author><author><name sortKey="Smits, Sl" uniqKey="Smits S">SL Smits</name></author><author><name sortKey="El Tahir, Ye" uniqKey="El Tahir Y">YE El Tahir</name></author><author><name sortKey="De Sousa, R" uniqKey="De Sousa R">R De Sousa</name></author><author><name sortKey="Van Beek, J" uniqKey="Van Beek J">J van Beek</name></author><author><name sortKey="Nowotny, N" uniqKey="Nowotny N">N Nowotny</name></author><author><name sortKey="Van Maanen, K" uniqKey="Van Maanen K">K van Maanen</name></author><author><name sortKey="Hidalgo Hermoso, E" uniqKey="Hidalgo Hermoso E">E Hidalgo-Hermoso</name></author><author><name sortKey="Bosch, Bj" uniqKey="Bosch B">BJ Bosch</name></author><author><name sortKey="Rottier, P" uniqKey="Rottier P">P Rottier</name></author><author><name sortKey="Osterhaus, A" uniqKey="Osterhaus A">A Osterhaus</name></author><author><name sortKey="Gortazar Schmidt, C" uniqKey="Gortazar Schmidt C">C Gortázar-Schmidt</name></author><author><name sortKey="Drosten, C" uniqKey="Drosten C">C Drosten</name></author><author><name sortKey="Koopmans, Mp" uniqKey="Koopmans M">MP Koopmans</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Reusken, Cb" uniqKey="Reusken C">CB Reusken</name></author><author><name sortKey="Messadi, L" uniqKey="Messadi L">L Messadi</name></author><author><name sortKey="Feyisa, A" uniqKey="Feyisa A">A Feyisa</name></author><author><name sortKey="Ularamu, H" uniqKey="Ularamu H">H Ularamu</name></author><author><name sortKey="Godeke, Gj" uniqKey="Godeke G">GJ Godeke</name></author><author><name sortKey="Danmarwa, A" uniqKey="Danmarwa A">A Danmarwa</name></author><author><name sortKey="Dawo, F" uniqKey="Dawo F">F Dawo</name></author><author><name sortKey="Jemli, M" uniqKey="Jemli M">M Jemli</name></author><author><name sortKey="Melaku, S" uniqKey="Melaku S">S Melaku</name></author><author><name sortKey="Shamaki, D" uniqKey="Shamaki D">D Shamaki</name></author><author><name sortKey="Woma, Y" uniqKey="Woma Y">Y Woma</name></author><author><name sortKey="Wungak, Y" uniqKey="Wungak Y">Y Wungak</name></author><author><name sortKey="Gebremedhin, Ez" uniqKey="Gebremedhin E">EZ Gebremedhin</name></author><author><name sortKey="Zutt, I" uniqKey="Zutt I">I Zutt</name></author><author><name sortKey="Bosch, Bj" uniqKey="Bosch B">BJ Bosch</name></author><author><name sortKey="Haagmans, Bl" uniqKey="Haagmans B">BL Haagmans</name></author><author><name sortKey="Koopmans, Mp" uniqKey="Koopmans M">MP Koopmans</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Sabir, Js" uniqKey="Sabir J">JS Sabir</name></author><author><name sortKey="Lam, Tt" uniqKey="Lam T">TT Lam</name></author><author><name sortKey="Ahmed, Mm" uniqKey="Ahmed M">MM Ahmed</name></author><author><name sortKey="Li, L" uniqKey="Li L">L Li</name></author><author><name sortKey="Shen, Y" uniqKey="Shen Y">Y Shen</name></author><author><name sortKey="Abo Aba, Se" uniqKey="Abo Aba S">SE Abo-Aba</name></author><author><name sortKey="Qureshi, Mi" uniqKey="Qureshi M">MI Qureshi</name></author><author><name sortKey="Abu Zeid, M" uniqKey="Abu Zeid M">M Abu-Zeid</name></author><author><name sortKey="Zhang, Y" uniqKey="Zhang Y">Y Zhang</name></author><author><name sortKey="Khiyami, Ma" uniqKey="Khiyami M">MA Khiyami</name></author><author><name sortKey="Alharbi, Ns" uniqKey="Alharbi N">NS Alharbi</name></author><author><name sortKey="Hajrah, Nh" uniqKey="Hajrah N">NH Hajrah</name></author><author><name sortKey="Sabir, Mj" uniqKey="Sabir M">MJ Sabir</name></author><author><name sortKey="Mutwakil, Mh" uniqKey="Mutwakil M">MH Mutwakil</name></author><author><name sortKey="Kabli, Sa" uniqKey="Kabli S">SA Kabli</name></author><author><name sortKey="Alsulaimany, Fa" uniqKey="Alsulaimany F">FA Alsulaimany</name></author><author><name sortKey="Obaid, Ay" uniqKey="Obaid A">AY Obaid</name></author><author><name sortKey="Zhou, B" uniqKey="Zhou B">B Zhou</name></author><author><name sortKey="Smith, Dk" uniqKey="Smith D">DK Smith</name></author><author><name sortKey="Holmes, Ec" uniqKey="Holmes E">EC Holmes</name></author><author><name sortKey="Zhu, H" uniqKey="Zhu H">H Zhu</name></author><author><name sortKey="Guan, Y" uniqKey="Guan Y">Y Guan</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Seong, Mw" uniqKey="Seong M">MW Seong</name></author><author><name sortKey="Kim, Sy" uniqKey="Kim S">SY Kim</name></author><author><name sortKey="Corman, Vm" uniqKey="Corman V">VM Corman</name></author><author><name sortKey="Kim, Ts" uniqKey="Kim T">TS Kim</name></author><author><name sortKey="Cho, Si" uniqKey="Cho S">SI Cho</name></author><author><name sortKey="Kim, Mj" uniqKey="Kim M">MJ Kim</name></author><author><name sortKey="Lee, Sj" uniqKey="Lee S">SJ Lee</name></author><author><name sortKey="Lee, Js" uniqKey="Lee J">JS Lee</name></author><author><name sortKey="Seo, Sh" uniqKey="Seo S">SH Seo</name></author><author><name sortKey="Ahn, Js" uniqKey="Ahn J">JS Ahn</name></author><author><name sortKey="Yu, Bs" uniqKey="Yu B">BS Yu</name></author><author><name sortKey="Park, N" uniqKey="Park N">N Park</name></author><author><name sortKey="Oh, Md" uniqKey="Oh M">MD Oh</name></author><author><name sortKey="Park, Wb" uniqKey="Park W">WB Park</name></author><author><name sortKey="Lee, Jy" uniqKey="Lee J">JY Lee</name></author><author><name sortKey="Kim, G" uniqKey="Kim G">G Kim</name></author><author><name sortKey="Joh, Js" uniqKey="Joh J">JS Joh</name></author><author><name sortKey="Jeong, I" uniqKey="Jeong I">I Jeong</name></author><author><name sortKey="Kim, Ec" uniqKey="Kim E">EC Kim</name></author><author><name sortKey="Drosten, C" uniqKey="Drosten C">C Drosten</name></author><author><name sortKey="Park, Ss" uniqKey="Park S">SS Park</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Smith, Gj" uniqKey="Smith G">GJ Smith</name></author><author><name sortKey="Bahl, J" uniqKey="Bahl J">J Bahl</name></author><author><name sortKey="Vijaykrishna, D" uniqKey="Vijaykrishna D">D Vijaykrishna</name></author><author><name sortKey="Zhang, J" uniqKey="Zhang J">J Zhang</name></author><author><name sortKey="Poon, Ll" uniqKey="Poon L">LL Poon</name></author><author><name sortKey="Chen, H" uniqKey="Chen H">H Chen</name></author><author><name sortKey="Webster, Rg" uniqKey="Webster R">RG Webster</name></author><author><name sortKey="Peiris, Js" uniqKey="Peiris J">JS Peiris</name></author><author><name sortKey="Guan, Y" uniqKey="Guan Y">Y Guan</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Turner, Tl" uniqKey="Turner T">TL Turner</name></author><author><name sortKey="Hahn, Mw" uniqKey="Hahn M">MW Hahn</name></author><author><name sortKey="Nuzhdin, Sv" uniqKey="Nuzhdin S">SV Nuzhdin</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Van Boheemen, S" uniqKey="Van Boheemen S">S van Boheemen</name></author><author><name sortKey="De Graaf, M" uniqKey="De Graaf M">M de Graaf</name></author><author><name sortKey="Lauber, C" uniqKey="Lauber C">C Lauber</name></author><author><name sortKey="Bestebroer, Tm" uniqKey="Bestebroer T">TM Bestebroer</name></author><author><name sortKey="Raj, Vs" uniqKey="Raj V">VS Raj</name></author><author><name sortKey="Zaki, Am" uniqKey="Zaki A">AM Zaki</name></author><author><name sortKey="Osterhaus, Ad" uniqKey="Osterhaus A">AD Osterhaus</name></author><author><name sortKey="Haagmans, Bl" uniqKey="Haagmans B">BL Haagmans</name></author><author><name sortKey="Gorbalenya, Ae" uniqKey="Gorbalenya A">AE Gorbalenya</name></author><author><name sortKey="Snijder, Ej" uniqKey="Snijder E">EJ Snijder</name></author><author><name sortKey="Fouchier, Ra" uniqKey="Fouchier R">RA Fouchier</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Vaughan, Tg" uniqKey="Vaughan T">TG Vaughan</name></author><author><name sortKey="Kuhnert, D" uniqKey="Kuhnert D">D Kühnert</name></author><author><name sortKey="Popinga, A" uniqKey="Popinga A">A Popinga</name></author><author><name sortKey="Welch, D" uniqKey="Welch D">D Welch</name></author><author><name sortKey="Drummond, Aj" uniqKey="Drummond A">AJ Drummond</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Volz, Em" uniqKey="Volz E">EM Volz</name></author><author><name sortKey="Koelle, K" uniqKey="Koelle K">K Koelle</name></author><author><name sortKey="Bedford, T" uniqKey="Bedford T">T Bedford</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Volz, Em" uniqKey="Volz E">EM Volz</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wernery, U" uniqKey="Wernery U">U Wernery</name></author><author><name sortKey="Corman, Vm" uniqKey="Corman V">VM Corman</name></author><author><name sortKey="Wong, Ey" uniqKey="Wong E">EY Wong</name></author><author><name sortKey="Tsang, Ak" uniqKey="Tsang A">AK Tsang</name></author><author><name sortKey="Muth, D" uniqKey="Muth D">D Muth</name></author><author><name sortKey="Lau, Sk" uniqKey="Lau S">SK Lau</name></author><author><name sortKey="Khazanehdari, K" uniqKey="Khazanehdari K">K Khazanehdari</name></author><author><name sortKey="Zirkel, F" uniqKey="Zirkel F">F Zirkel</name></author><author><name sortKey="Ali, M" uniqKey="Ali M">M Ali</name></author><author><name sortKey="Nagy, P" uniqKey="Nagy P">P Nagy</name></author><author><name sortKey="Juhasz, J" uniqKey="Juhasz J">J Juhasz</name></author><author><name sortKey="Wernery, R" uniqKey="Wernery R">R Wernery</name></author><author><name sortKey="Joseph, S" uniqKey="Joseph S">S Joseph</name></author><author><name sortKey="Syriac, G" uniqKey="Syriac G">G Syriac</name></author><author><name sortKey="Elizabeth, Sk" uniqKey="Elizabeth S">SK Elizabeth</name></author><author><name sortKey="Patteril, Na" uniqKey="Patteril N">NA Patteril</name></author><author><name sortKey="Woo, Pc" uniqKey="Woo P">PC Woo</name></author><author><name sortKey="Drosten, C" uniqKey="Drosten C">C Drosten</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wernery, U" uniqKey="Wernery U">U Wernery</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Xie, Q" uniqKey="Xie Q">Q Xie</name></author><author><name sortKey="Cao, Y" uniqKey="Cao Y">Y Cao</name></author><author><name sortKey="Su, J" uniqKey="Su J">J Su</name></author><author><name sortKey="Wu, X" uniqKey="Wu X">X Wu</name></author><author><name sortKey="Wan, C" uniqKey="Wan C">C Wan</name></author><author><name sortKey="Ke, C" uniqKey="Ke C">C Ke</name></author><author><name sortKey="Zhao, W" uniqKey="Zhao W">W Zhao</name></author><author><name sortKey="Zhang, B" uniqKey="Zhang B">B Zhang</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Yang, Z" uniqKey="Yang Z">Z Yang</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zaki, Am" uniqKey="Zaki A">AM Zaki</name></author><author><name sortKey="Van Boheemen, S" uniqKey="Van Boheemen S">S van Boheemen</name></author><author><name sortKey="Bestebroer, Tm" uniqKey="Bestebroer T">TM Bestebroer</name></author><author><name sortKey="Osterhaus, Ad" uniqKey="Osterhaus A">AD Osterhaus</name></author><author><name sortKey="Fouchier, Ra" uniqKey="Fouchier R">RA Fouchier</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zhang, Z" uniqKey="Zhang Z">Z Zhang</name></author><author><name sortKey="Shen, L" uniqKey="Shen L">L Shen</name></author><author><name sortKey="Gu, X" uniqKey="Gu X">X Gu</name></author></analytic></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">eLife</journal-id><journal-id journal-id-type="iso-abbrev">Elife</journal-id><journal-id journal-id-type="publisher-id">eLife</journal-id><journal-title-group><journal-title>eLife</journal-title></journal-title-group><issn pub-type="epub">2050-084X</issn><publisher><publisher-name>eLife Sciences Publications, Ltd</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">29336306</article-id><article-id pub-id-type="pmc">5777824</article-id><article-id pub-id-type="publisher-id">31257</article-id><article-id pub-id-type="doi">10.7554/eLife.31257</article-id><article-categories><subj-group subj-group-type="display-channel"><subject>Research Article</subject></subj-group><subj-group subj-group-type="heading"><subject>Epidemiology and Global Health</subject></subj-group><subj-group subj-group-type="heading"><subject>Genomics and Evolutionary Biology</subject></subj-group></article-categories><title-group><article-title>MERS-CoV spillover at the camel-human interface</article-title></title-group><contrib-group><contrib id="author-83449" contrib-type="author" corresp="yes"><name><surname>Dudas</surname><given-names>Gytis</given-names></name><contrib-id authenticated="true" contrib-id-type="orcid">http://orcid.org/0000-0002-0227-4158</contrib-id><email>gdudas@fredhutch.org</email><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="other" rid="fund5"></xref><xref ref-type="fn" rid="con1"></xref><xref ref-type="fn" rid="conf1"></xref></contrib><contrib id="author-95869" contrib-type="author"><name><surname>Carvalho</surname><given-names>Luiz Max</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="fn" rid="con2"></xref><xref ref-type="fn" rid="conf1"></xref></contrib><contrib id="author-4769" contrib-type="author"><name><surname>Rambaut</surname><given-names>Andrew</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff3">3</xref><xref ref-type="other" rid="fund3"></xref><xref ref-type="other" rid="fund4"></xref><xref ref-type="other" rid="fund6"></xref><xref ref-type="fn" rid="con3"></xref><xref ref-type="fn" rid="conf1"></xref></contrib><contrib id="author-9070" contrib-type="author"><name><surname>Bedford</surname><given-names>Trevor</given-names></name><contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0002-4039-5794</contrib-id><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="other" rid="fund1"></xref><xref ref-type="other" rid="fund2"></xref><xref ref-type="fn" rid="con4"></xref><xref ref-type="fn" rid="conf1"></xref></contrib><aff id="aff1"><label>1</label><institution content-type="dept">Vaccine and Infectious Disease Division</institution><institution>Fred Hutchinson Cancer Research Center</institution><addr-line>Seattle</addr-line><country>United States</country></aff><aff id="aff2"><label>2</label><institution content-type="dept">Institute of Evolutionary Biology</institution><institution>University of Edinburgh</institution><addr-line>Edinburgh</addr-line><country>United Kingdom</country></aff><aff id="aff3"><label>3</label><institution content-type="dept">Fogarty International Center</institution><institution>National Institutes of Health</institution><addr-line>Bethesda</addr-line><country>United States</country></aff></contrib-group><contrib-group><contrib id="author-12065" contrib-type="editor"><name><surname>Ferguson</surname><given-names>Neil M</given-names></name><role>Reviewing Editor</role><aff id="aff4"><institution>Imperial College London</institution><country>United Kingdom</country></aff></contrib></contrib-group><pub-date date-type="pub" publication-format="electronic"><day>16</day><month>1</month><year>2018</year></pub-date><pub-date pub-type="collection"><year>2018</year></pub-date><volume>7</volume><elocation-id>e31257</elocation-id><history><date date-type="received" iso-8601-date="2017-08-14"><day>14</day><month>8</month><year>2017</year></date><date date-type="accepted" iso-8601-date="2017-12-19"><day>19</day><month>12</month><year>2017</year></date></history><permissions><copyright-statement>© 2018, Dudas et al</copyright-statement><copyright-year>2018</copyright-year><copyright-holder>Dudas et al</copyright-holder><ali:free_to_read></ali:free_to_read><license xlink:href="http://creativecommons.org/licenses/by/4.0/"><ali:license_ref>http://creativecommons.org/licenses/by/4.0/</ali:license_ref><license-p>This article is distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>, which permits unrestricted use and redistribution provided that the original author and source are credited.</license-p></license></permissions><self-uri content-type="pdf" xlink:href="elife-31257.pdf"></self-uri><abstract><p>Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic virus from camels causing significant mortality and morbidity in humans in the Arabian Peninsula. The epidemiology of the virus remains poorly understood, and while case-based and seroepidemiological studies have been employed extensively throughout the epidemic, viral sequence data have not been utilised to their full potential. Here, we use existing MERS-CoV sequence data to explore its phylodynamics in two of its known major hosts, humans and camels. We employ structured coalescent models to show that long-term MERS-CoV evolution occurs exclusively in camels, whereas humans act as a transient, and ultimately terminal host. By analysing the distribution of human outbreak cluster sizes and zoonotic introduction times, we show that human outbreaks in the Arabian peninsula are driven by seasonally varying zoonotic transfer of viruses from camels. Without heretofore unseen evolution of host tropism, MERS-CoV is unlikely to become endemic in humans.</p></abstract><abstract abstract-type="executive-summary"><title>eLife digest</title><p>Coronaviruses are one of many groups of viruses that cause the common cold, though some members of the group can cause more serious illnesses. The SARS coronavirus, for example, caused a widespread epidemic of pneumonia in 2003 that killed 774 people. In 2012, a new coronavirus was detected in patients from the Arabian Peninsula with severe respiratory symptoms known as Middle East respiratory syndrome (or MERS for short). To date the MERS coronavirus has also killed over 700 people (albeit over a number of years rather than months). Yet unlike the SARS coronavirus that spreads efficiently between humans, cases of MERS were rarely linked to each other or to contact with animals, with the exception of hospital outbreaks.</p><p>Though camels were later identified as the original source of MERS coronavirus infections in humans, the role of these animals in the epidemic was not well understood. Throughout the epidemic nearly 300 genomes of the MERS coronavirus had been sequenced, from both camels and humans. Previous attempts to understand the MERS epidemic had either relied on these data or reports of case numbers but led to conflicting results, at odds with other sources of evidence.</p><p>Dudas et al. wanted to work out how many times the MERS coronavirus had been introduced into humans from camels. If it happened once, this would indicate that the virus is good at spreading between humans and that treating human cases should be a priority. However, if every human case occurred as a new introduction of the MERS coronavirus from camels, this would mean that the human epidemic would not stop until the virus is controlled at the source, that is, in camels. Many scientists had argued that the second of these scenarios was most likely, but this had not been strongly demonstrated with data.</p><p>By looking at the already sequenced genomes, Dudas et al. worked out how the MERS coronaviruses were related to each other, and reconstructed their family tree. Information about the host from which each sequence was collected was then mapped on the tree. Unlike previous attempts to complete this kind of analysis, Dudas et al. took an approach that could deal with the viruses in camels being more diverse than those in humans.</p><p>Consistent with the scenario where human cases occurred as new introductions from camels, the analysis showed that the MERS coronavirus populations is maintained exclusively in camels and the viruses seen in humans are evolutionary dead-ends. This suggests that MERS coronavirus spreads poorly between humans, and has instead jumped from camels to humans hundreds of times since 2012.</p><p>As well as providing data to confirm a previously suspected hypothesis, these findings provide more support to the current plans to mitigate infections with MERS coronavirus in the Arabian Peninsula by focusing control efforts on camels.</p></abstract><kwd-group kwd-group-type="author-keywords"><kwd>phylogenetics</kwd><kwd>phylodynamics</kwd><kwd>MERS</kwd><kwd>coronavirus</kwd><kwd>zoonosis</kwd><kwd>structured coalescent</kwd></kwd-group><kwd-group kwd-group-type="research-organism"><title>Research organism</title><kwd>Virus</kwd></kwd-group><funding-group><award-group id="fund1"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000002</institution-id><institution>National Institutes of Health</institution></institution-wrap></funding-source><award-id>R35 GM119774-01</award-id><principal-award-recipient><name><surname>Bedford</surname><given-names>Trevor</given-names></name></principal-award-recipient></award-group><award-group id="fund2"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000875</institution-id><institution>Pew Charitable Trusts</institution></institution-wrap></funding-source><award-id>Pew Biomedical Scholar</award-id><principal-award-recipient><name><surname>Bedford</surname><given-names>Trevor</given-names></name></principal-award-recipient></award-group><award-group id="fund3"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/501100000780</institution-id><institution>European Commission</institution></institution-wrap></funding-source><award-id>278433-PREDEMICS</award-id><principal-award-recipient><name><surname>Rambaut</surname><given-names>Andrew</given-names></name></principal-award-recipient></award-group><award-group id="fund4"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100010269</institution-id><institution>Wellcome</institution></institution-wrap></funding-source><award-id>206298/Z/17/Z</award-id><principal-award-recipient><name><surname>Rambaut</surname><given-names>Andrew</given-names></name></principal-award-recipient></award-group><award-group id="fund5"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100005895</institution-id><institution>Fred Hutchinson Cancer Research Center</institution></institution-wrap></funding-source><award-id>Mahan Postdoctoral Fellowship</award-id><principal-award-recipient><name><surname>Dudas</surname><given-names>Gytis</given-names></name></principal-award-recipient></award-group><award-group id="fund6"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/501100000780</institution-id><institution>European Commission</institution></institution-wrap></funding-source><award-id>725422-RESERVOIRDOCS</award-id><principal-award-recipient><name><surname>Rambaut</surname><given-names>Andrew</given-names></name></principal-award-recipient></award-group><funding-statement>The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.</funding-statement></funding-group><custom-meta-group><custom-meta specific-use="meta-only"><meta-name>Author impact statement</meta-name><meta-value>MERS-CoV infections in the Arabian Peninsula are the result of several hundred spillover events from viruses circulating in camels into the human population.</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec sec-type="intro" id="s1"><title>Introduction</title><p>Middle East respiratory syndrome coronavirus (MERS-CoV), endemic in camels in the Arabian Peninsula, is the causative agent of zoonotic infections and limited outbreaks in humans. The virus, first discovered in 2012 (<xref rid="bib99" ref-type="bibr">Zaki et al., 2012</xref>; <xref rid="bib88" ref-type="bibr">van Boheemen et al., 2012</xref>), has caused more than 2000 infections and over 700 deaths, according to the World Health Organization (WHO) (<xref rid="bib96" ref-type="bibr">World Health Organization, 2017</xref>). Its epidemiology remains obscure, largely because infections are observed among the most severely affected individuals, such as older males with comorbidities (<xref rid="bib6" ref-type="bibr">Assiri et al., 2013a</xref>; <xref rid="bib94" ref-type="bibr">WHO MERS-Cov Research Group, 2013</xref>). While contact with camels is often reported, other patients do not recall contact with any livestock, suggesting an unobserved community contribution to the outbreak (<xref rid="bib94" ref-type="bibr">WHO MERS-Cov Research Group, 2013</xref>). Previous studies on MERS-CoV epidemiology have used serology to identify factors associated with MERS-CoV exposure in potential risk groups (<xref rid="bib81" ref-type="bibr">Reusken et al., 2015</xref>; <xref rid="bib82" ref-type="bibr">Reusken et al., 2013</xref>). Such data have shown high seroprevalence in camels (<xref rid="bib70" ref-type="bibr">Müller et al., 2014</xref>; <xref rid="bib21" ref-type="bibr">Corman et al., 2014</xref>; <xref rid="bib20" ref-type="bibr">Chu et al., 2014</xref>; <xref rid="bib82" ref-type="bibr">Reusken et al., 2013</xref>; <xref rid="bib83" ref-type="bibr">Reusken et al., 2014</xref>) and evidence of contact with MERS-CoV in workers with occupational exposure to camels (<xref rid="bib81" ref-type="bibr">Reusken et al., 2015</xref>; <xref rid="bib71" ref-type="bibr">Müller et al., 2015</xref>). Separately, epidemiological modelling approaches have been used to look at incidence reports through time, space and across hosts (<xref rid="bib18" ref-type="bibr">Cauchemez et al., 2016</xref>).</p><p>Although such epidemiological approaches yield important clues about exposure patterns and potential for larger outbreaks, much inevitably remains opaque to such approaches due to difficulties in linking cases into transmission clusters in the absence of detailed information. Where sequence data are relatively cheap to produce, genomic epidemiological approaches can fill this critical gap in outbreak scenarios (<xref rid="bib61" ref-type="bibr">Liu et al., 2013</xref>; <xref rid="bib37" ref-type="bibr">Gire et al., 2014</xref>; <xref rid="bib38" ref-type="bibr">Grubaugh et al., 2017</xref>). These data often yield a highly detailed picture of an epidemic when complete genome sequencing is performed consistently and appropriate metadata collected (<xref rid="bib30" ref-type="bibr">Dudas et al., 2017</xref>). Sequence data can help discriminate between multiple and single source scenarios (<xref rid="bib37" ref-type="bibr">Gire et al., 2014</xref>; <xref rid="bib77" ref-type="bibr">Quick et al., 2015</xref>), which are fundamental to quantifying risk (<xref rid="bib38" ref-type="bibr">Grubaugh et al., 2017</xref>). Sequencing MERS-CoV has been performed as part of initial attempts to link human infections with the camel reservoir (<xref rid="bib68" ref-type="bibr">Memish et al., 2014</xref>), nosocomial outbreak investigations (<xref rid="bib7" ref-type="bibr">Assiri et al., 2013b</xref>) and routine surveillance (<xref rid="bib92" ref-type="bibr">Wernery et al., 2015</xref>). A large portion of MERS-CoV sequences come from outbreaks within hospitals, where sequence data have been used to determine whether infections were isolated introductions or were part of a larger hospital-associated outbreak (<xref rid="bib33" ref-type="bibr">Fagbo et al., 2015</xref>). Similar studies on MERS-CoV have taken place at broader geographic scales, such as cities (<xref rid="bib22" ref-type="bibr">Cotten et al., 2013</xref>).</p><p>It is widely accepted that recorded human MERS-CoV infections are a result of at least several introductions of the virus into humans (<xref rid="bib22" ref-type="bibr">Cotten et al., 2013</xref>) and that contact with camels is a major risk factor for developing MERS, per WHO guidelines (<xref rid="bib95" ref-type="bibr">World Health Organization, 2016</xref>). Previous studies attempting to quantify the actual number of spillover infections have either relied on case-based epidemiological approaches (<xref rid="bib18" ref-type="bibr">Cauchemez et al., 2016</xref>) or employed methods agnostic to signals of population structure within sequence data (<xref rid="bib100" ref-type="bibr">Zhang et al., 2016</xref>). Here, we use a dataset of 274 MERS-CoV genomes to investigate transmission patterns of the virus between humans and camels.</p><p>Here, we use an explicit model of metapopulation structure and migration between discrete subpopulations, referred to here as demes (<xref rid="bib89" ref-type="bibr">Vaughan et al., 2014</xref>), derived from the structured coalescent (<xref rid="bib72" ref-type="bibr">Notohara, 1990</xref>). Unlike approaches that model host species as a discrete phylogenetic trait of the virus using continuous-time Markov processes (or simpler, parsimony based, approaches) (<xref rid="bib34" ref-type="bibr">Faria et al., 2013</xref>; <xref rid="bib64" ref-type="bibr">Lycett et al., 2016</xref>), population structure models explicitly incorporate contrasts in deme effective population sizes and migration between demes. By estimating independent coalescence rates for MERS-CoV in humans and camels, as well as migration patterns between the two demes, we show that long-term viral evolution of MERS-CoV occurs exclusively in camels. Our results suggest that spillover events into humans are seasonal and might be associated with the calving season in camels. However, we find that MERS-CoV, once introduced into humans, follows transient transmission chains that soon abate. Using Monte Carlo simulations we show that <inline-formula><mml:math id="inf1"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> for MERS-CoV circulating in humans is much lower than the epidemic threshold of 1.0 and that correspondingly the virus has been introduced into humans hundreds of times.</p></sec><sec sec-type="results" id="s2"><title>Results</title><sec id="s2-1"><title>MERS-CoV is predominantly a camel virus</title><p>The structured coalescent approach we employ (see Materials and methods) identifies camels as a reservoir host where most of MERS-CoV evolution takes place (<xref ref-type="fig" rid="fig1">Figure 1</xref>), while human MERS outbreaks are transient and terminal with respect to long-term evolution of the virus (<xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1</xref>). Across 174 MERS-CoV genomes collected from humans, we estimate a median of 56 separate camel-to-human cross-species transmissions (95% highest posterior density (HPD): 48–63). While we estimate a median of 3 (95% HPD: 0–12) human-to-camel migrations, the 95% HPD interval includes zero and we find that no such migrations are found in the maximum clade credibility tree (<xref ref-type="fig" rid="fig1">Figure 1</xref>). Correspondingly, we observe substantially higher camel-to-human migration rate estimates than human-to-camel migration rate estimates (<xref ref-type="fig" rid="fig1s2">Figure 1—figure supplement 2</xref>). This inference derives from the tree structure wherein human viruses appear as clusters of highly related sequences nested within the diversity seen in camel viruses, which themselves show significantly higher diversity and less clustering. This manifests as different rates of coalescence with camel viruses showing a scaled effective population size <inline-formula><mml:math id="inf2"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo></mml:mo><mml:mi>τ</mml:mi></mml:mrow></mml:math></inline-formula> of 3.49 years (95% HPD: 2.71–4.38) and human viruses showing a scaled effective population of 0.24 years (95% HPD: 0.14–0.34).</p><fig id="fig1" position="float" orientation="portrait"><object-id pub-id-type="doi">10.7554/eLife.31257.003</object-id><label>Figure 1.</label><caption><title>Typed maximum clade credibility tree of MERS-CoV genomes from 174 human viruses and 100 camel viruses.</title><p>Maximum clade credibility (MCC) tree showing inferred ancestral hosts for MERS-CoV recovered with the structured coalescent. The vast majority of MERS-CoV evolution is inferred to occur in camels (orange) with human outbreaks (blue) representing evolutionary dead-ends for the virus. Confidence in host assignment is depicted as a colour gradient, with increased uncertainty in host assignment (posterior probabilities close to 0.5) shown as grey. While large clusters of human cases are apparent in the tree, significant contributions to human outbreaks are made by singleton sequences, likely representing recent cross-species transmissions that were caught early.</p><p><supplementary-material content-type="local-data" id="fig1sdata1"><object-id pub-id-type="doi">10.7554/eLife.31257.009</object-id><label>Figure 1—source data 1.</label><caption><title>XML to run structured coalescent analysis and output files.</title></caption><media mime-subtype="zip" mimetype="application" xlink:href="elife-31257-fig1-data1.zip" orientation="portrait" id="d35e510" position="anchor"></media></supplementary-material></p><p><supplementary-material content-type="local-data" id="fig1sdata2"><object-id pub-id-type="doi">10.7554/eLife.31257.010</object-id><label>Figure 1—source data 2.</label><caption><title>XML to run structured coalescent analysis with a relaxed prior and output file.</title></caption><media mime-subtype="zip" mimetype="application" xlink:href="elife-31257-fig1-data2.zip" orientation="portrait" id="d35e520" position="anchor"></media></supplementary-material></p><p><supplementary-material content-type="local-data" id="fig1sdata3"><object-id pub-id-type="doi">10.7554/eLife.31257.011</object-id><label>Figure 1—source data 3.</label><caption><title>XML to run discrete trait analysis (DTA) and output files.</title></caption><media mime-subtype="zip" mimetype="application" xlink:href="elife-31257-fig1-data3.zip" orientation="portrait" id="d35e530" position="anchor"></media></supplementary-material></p><p><supplementary-material content-type="local-data" id="fig1sdata4"><object-id pub-id-type="doi">10.7554/eLife.31257.012</object-id><label>Figure 1—source data 4.</label><caption><title>XML to run structured coalescent analysis with equal deme sizes between humans and camels and output files.</title></caption><media mime-subtype="zip" mimetype="application" xlink:href="elife-31257-fig1-data4.zip" orientation="portrait" id="d35e540" position="anchor"></media></supplementary-material></p><p><supplementary-material content-type="local-data" id="fig1sdata5"><object-id pub-id-type="doi">10.7554/eLife.31257.013</object-id><label>Figure 1—source data 5.</label><caption><title>Maximum likelihood phylogeny.</title></caption><media mime-subtype="zip" mimetype="application" xlink:href="elife-31257-fig1-data5.zip" orientation="portrait" id="d35e550" position="anchor"></media></supplementary-material></p></caption><graphic xlink:href="elife-31257-fig1"></graphic><p content-type="supplemental-figure"><fig id="fig1s1" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.004</object-id><label>Figure 1—figure supplement 1.</label><caption><title>Evolutionary history of MERS-CoV partitioned between camels and humans.</title><p>This is the same tree as shown in <xref ref-type="fig" rid="fig1">Figure 1</xref>, but with contiguous stretches of MERS-CoV evolutionary history split by inferred host: camels (top in orange) and humans (bottom in blue). This visualisation highlights the ephemeral nature of MERS-CoV outbreaks in humans, compared to continuous circulation of the virus in camels.</p></caption><graphic xlink:href="elife-31257-fig1-figsupp1"></graphic></fig></p><p content-type="supplemental-figure"><fig id="fig1s2" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.005</object-id><label>Figure 1—figure supplement 2.</label><caption><title>Posterior backwards migration rate estimates for two choices of prior.</title><p>Negligible flow of MERS-CoV lineages from humans into camels is recovered regardless of prior choice (note that rates are backwards in time). Plots show the 95% highest posterior density for the estimated migration rate from the human deme into the camel deme looking backwards in time (orange) and <italic>vice versa</italic> (blue). Dotted lines indicate exponential priors specified for migration rates, with mean 1.0 (bottom) or 10.0 (top).</p></caption><graphic xlink:href="elife-31257-fig1-figsupp2"></graphic></fig></p><p content-type="supplemental-figure"><fig id="fig1s3" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.006</object-id><label>Figure 1—figure supplement 3.</label><caption><title>Maximum clade credibility (MCC) tree with ancestral state reconstruction according to a discrete trait model.</title><p>MCC tree is presented the same as <xref ref-type="fig" rid="fig1">Figure 1</xref> and <xref ref-type="fig" rid="fig1s4">Figure 1—figure supplement 4</xref>, with colours indicating the most probable state reconstruction at internal nodes. Unlike the structured coalescent summary shown in <xref ref-type="fig" rid="fig1">Figure 1</xref> where camels are reconstructed as the main host where MERS-CoV persists, the discrete trait approach identifies both camels and humans as major hosts with humans being the source of MERS-CoV infection in camels.</p></caption><graphic xlink:href="elife-31257-fig1-figsupp3"></graphic></fig></p><p content-type="supplemental-figure"><fig id="fig1s4" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.007</object-id><label>Figure 1—figure supplement 4.</label><caption><title>Maximum clade credibility (MCC) tree of structured coalescent model with enforced equal coalescence rates.</title><p>MCC tree is presented the same as <xref ref-type="fig" rid="fig1">Figure 1</xref> and <xref ref-type="fig" rid="fig1s3">Figure 1—figure supplement 3</xref>, with colours indicating the most probable state reconstruction at internal nodes. Similar to <xref ref-type="fig" rid="fig1s3">Figure 1—figure supplement 3</xref> enforcing equal coalescence rates between demes in a structured coalescent model identifies humans as a major MERS-CoV host and the source of viruses in camels.</p></caption><graphic xlink:href="elife-31257-fig1-figsupp4"></graphic></fig></p><p content-type="supplemental-figure"><fig id="fig1s5" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.008</object-id><label>Figure 1—figure supplement 5.</label><caption><title>Maximum likelihood (ML) tree of MERS-CoV genomes coloured by origin of sequence.</title><p>Maximum likelihood tree shows genetic divergence between MERS-CoV genomes collected from camels (orange tips) and humans (blue tips).</p></caption><graphic xlink:href="elife-31257-fig1-figsupp5"></graphic></fig></p></fig><p>We believe that the small number of inferred human-to-camel migrations are induced by the migration rate prior, while some are derived from phylogenetic proximity of human sequences to the apparent ‘backbone’ of the phylogenetic tree. This is most apparent in lineages in early-mid 2013 that lead up to sequences comprising the MERS-CoV clade dominant in 2015, where owing to poor sampling of MERS-CoV genetic diversity from camels the model cannot completely dismiss humans as a potential alternative host. The first sequences of MERS-CoV from camels do not appear in our data until November 2013. Our finding of negligible human-to-camel transmission is robust to choice of prior (<xref ref-type="fig" rid="fig1s2">Figure 1—figure supplement 2</xref>).</p><p>The repeated and asymmetric introductions of short-lived clusters of MERS-CoV sequences from camels into humans leads us to conclude that MERS-CoV epidemiology in humans is dominated by zoonotic transmission (<xref ref-type="fig" rid="fig1">Figure 1</xref> and <xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1</xref>). We observe dense terminal clusters of MERS-CoV circulating in humans that are of no subsequent relevance to the evolution of the virus. These clusters of presumed human-to-human transmission are then embedded within extensive diversity of MERS-CoV lineages inferred to be circulating in camels, a classic pattern of source-sink dynamics. Our findings suggest that instances of human infection with MERS-CoV are more common than currently thought, with exceedingly short transmission chains mostly limited to primary cases that might be mild and ultimately not detected by surveillance or sequencing. Structured coalescent analyses recover the camel-centered picture of MERS-CoV evolution despite sequence data heavily skewed towards non-uniformly sampled human cases and are robust to choice of prior. Comparing these results with a currently standard discrete trait analysis (<xref rid="bib59" ref-type="bibr">Lemey et al., 2009</xref>) approach for ancestral state reconstruction shows dramatic differences in host reconstruction at internal nodes (<xref ref-type="fig" rid="fig1s3">Figure 1—figure supplement 3</xref>). Discrete trait analysis reconstruction identifies both camels and humans as important hosts for MERS-CoV persistence, but with humans as the ultimate source of camel infections. A similar approach has been attempted previously (<xref rid="bib100" ref-type="bibr">Zhang et al., 2016</xref>), but this interpretation of MERS-CoV evolution disagrees with lack of continuing human transmission chains outside of Arabian peninsula, low seroprevalence in humans and very high seroprevalence in camels across Saudi Arabia. We suspect that this particular discrete trait analysis reconstruction is false due to biased data, that is, having nearly twice as many MERS-CoV sequences from humans (<inline-formula><mml:math id="inf3"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>174</mml:mn></mml:mrow></mml:math></inline-formula>) than from camels (<inline-formula><mml:math id="inf4"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>100</mml:mn></mml:mrow></mml:math></inline-formula>) and the inability of the model to account for and quantify vastly different rates of coalescence in the phylogenetic vicinity of both types of sequences. We can replicate these results by either applying the same model to current data (<xref ref-type="fig" rid="fig1s3">Figure 1—figure supplement 3</xref>) or by enforcing equal coalescence rates within each deme in the structured coalescent model (<xref ref-type="fig" rid="fig1s4">Figure 1—figure supplement 4</xref>).</p></sec><sec id="s2-2"><title>MERS-CoV shows seasonal introductions</title><p>We use the posterior distribution of MERS-CoV introduction events from camels to humans (<xref ref-type="fig" rid="fig1">Figure 1</xref>) to model seasonal variation in zoonotic transfer of viruses. We identify four months (April, May, June, July) when the odds of MERS-CoV introductions are increased (<xref ref-type="fig" rid="fig2">Figure 2</xref>) and four when the odds are decreased (August, September, November, December). Camel calving is reported to occur from October to February (<xref rid="bib4" ref-type="bibr">Almutairi et al., 2010</xref>), with rapidly declining maternal antibody levels in calves within the first weeks after birth (<xref rid="bib93" ref-type="bibr">Wernery, 2001</xref>). It is possible that MERS-CoV sweeps through each new camel generation once critical mass of susceptibles is reached (<xref rid="bib67" ref-type="bibr">Martinez-Bakker et al., 2014</xref>), leading to a sharp rise in prevalence of the virus in camels and resulting in increased force of infection into the human population. Strong influx of susceptibles and subsequent sweeping outbreaks in camels may explain evidence of widespread exposure to MERS-CoV in camels from seroepidemiology (<xref rid="bib70" ref-type="bibr">Müller et al., 2014</xref>; <xref rid="bib21" ref-type="bibr">Corman et al., 2014</xref>; <xref rid="bib20" ref-type="bibr">Chu et al., 2014</xref>; <xref rid="bib82" ref-type="bibr">Reusken et al., 2013</xref>; <xref rid="bib83" ref-type="bibr">Reusken et al., 2014</xref>).</p><fig id="fig2" orientation="portrait" position="float"><object-id pub-id-type="doi">10.7554/eLife.31257.014</object-id><label>Figure 2.</label><caption><title>Seasonality of MERS-CoV introduction events.</title><p>(<bold>A</bold>) Posterior density estimates partitioned by month showing the 95% highest posterior density interval for relative odds ratios of MERS-CoV introductions into humans. Posterior means are indicated with circles. Evidence for increased or decreased risk (95% HPD excludes 1.0) for introductions are indicated by black or white circles, respectively. Hatched area spanning October to February indicates the camel calving season. (<bold>B</bold>) Sequence cluster sizes and inferred dates of introduction events. Each introduction event is shown as a vertical line positioned based on the median introduction time, as recovered by structured coalescent analyses and coloured by time of year with height indicating number of descendant sequences recovered from human cases. 95% highest posterior density intervals for introductions of MERS-CoV into humans are indicated with coloured lines, coloured by median estimated introduction time. The black dotted line indicates the joint probability density for introductions. We find little correlation between date and size of introduction (Spearman <inline-formula><mml:math id="inf5"><mml:mrow><mml:mi>ρ</mml:mi><mml:mo>=</mml:mo><mml:mn>0.06</mml:mn></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="inf6"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn>0.68</mml:mn></mml:mrow></mml:math></inline-formula>).</p><p><supplementary-material content-type="local-data" id="fig2sdata1"><object-id pub-id-type="doi">10.7554/eLife.31257.015</object-id><label>Figure 2—source data 1.</label><caption><title>MCMC samples from seasonality inference analysis. </title></caption><media mime-subtype="zip" mimetype="application" xlink:href="elife-31257-fig2-data1.zip" orientation="portrait" id="d35e761" position="anchor"></media></supplementary-material></p></caption><graphic xlink:href="elife-31257-fig2"></graphic></fig><p>Although we find evidence of seasonality in zoonotic spillover timing, no such relationship exists for sizes of human sequence clusters (<xref ref-type="fig" rid="fig2">Figure 2B</xref>). This is entirely expected, since little seasonality in human behaviour that could facilitate MERS-CoV transmission is expected following an introduction. Similarly, we do not observe any trend in human sequence cluster sizes over time (<xref ref-type="fig" rid="fig2">Figure 2B</xref>, Spearman <inline-formula><mml:math id="inf7"><mml:mrow><mml:mi>ρ</mml:mi><mml:mo>=</mml:mo><mml:mn>0.06</mml:mn></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="inf8"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn>0.68</mml:mn></mml:mrow></mml:math></inline-formula>), suggesting that MERS-CoV outbreaks in humans are neither growing nor shrinking in size. This is not surprising either, since MERS-CoV is a camel virus that has to date, experienced little-to-no selective pressure to improve transmissibility between humans.</p></sec><sec id="s2-3"><title>MERS-CoV is poorly suited for human transmission</title><p>Structured coalescent approaches clearly show humans to be a terminal host for MERS-CoV, implying poor transmissibility. However, we wanted to translate this observation into an estimate of the basic reproductive number <inline-formula><mml:math id="inf9"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> to provide an intuitive epidemic behaviour metric that does not require expertise in reading phylogenies. The parameter <inline-formula><mml:math id="inf10"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> determines expected number of secondary cases in a single infections as well as the distribution of total cases that result from a single introduction event into the human population (<xref ref-type="disp-formula" rid="equ2">Equation 1</xref>, Materials and methods). We estimate <inline-formula><mml:math id="inf11"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> along with other relevant parameters via Monte Carlo simulation in two steps. First, we simulate case counts across multiple outbreaks totaling 2000 cases using <xref ref-type="disp-formula" rid="equ2">Equation 1</xref> and then we subsample from each case cluster to simulate sequencing of a fraction of cases. Sequencing simulations are performed via a multivariate hypergeometric distribution, where the probability of sequencing from a particular cluster depends on available sequencing capacity (number of trials), numbers of cases in the cluster (number of successes) and number of cases outside the cluster (number of failures). In addition, each hypergeometric distribution used to simulate sequencing is concentrated via a bias parameter, that enriches for large sequence clusters at the expense of smaller ones (for its effects see <xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1</xref>). This is a particularly pressing issue, since <italic>a priori</italic> we expect large hospital outbreaks of MERS to be overrepresented in sequence data, whereas sequences from primary cases will be sampled exceedingly rarely. We record the number, mean, standard deviation and skewness (third standardised moment) of sequence cluster sizes in each simulation (left-hand panel in <xref ref-type="fig" rid="fig3">Figure 3</xref>) and extract the subset of Monte Carlo simulations in which these summary statistics fall within the 95% highest posterior density observed in the empirical MERS-CoV data from structured coalescent analyses. We record <inline-formula><mml:math id="inf12"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> values, as well as the number of case clusters (equivalent to number of zoonotic introductions), for these empirically matched simulations. A schematic of this Monte Carlo procedure is shown in <xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2</xref>. Since the total number of cases is fixed at 2000, higher <inline-formula><mml:math id="inf13"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> results in fewer larger transmission clusters, while lower <inline-formula><mml:math id="inf14"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> results in many smaller transmission clusters.</p><fig id="fig3" position="float" orientation="portrait"><object-id pub-id-type="doi">10.7554/eLife.31257.016</object-id><label>Figure 3.</label><caption><title>Monte Carlo simulations of human transmission clusters.</title><p>Leftmost scatter plot shows the distribution of individual Monte Carlo simulation sequence cluster size statistics (mean and skewness) coloured by the <inline-formula><mml:math id="inf15"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> value used for the simulation. The dotted rectangle identifies the 95% highest posterior density bounds for sequence cluster size mean and skewness observed for empirical MERS-CoV data. The distribution of <inline-formula><mml:math id="inf16"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> values that fall within 95% HPDs for sequence cluster size mean, standard deviation, skewness and number of introductions, is shown in the middle, on the same <inline-formula><mml:math id="inf17"><mml:mi>y</mml:mi></mml:math></inline-formula>-axis. Bins falling inside the 95% percentiles are coloured by <inline-formula><mml:math id="inf18"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula>, as in the leftmost scatter plot. The distribution of total number of introductions associated with simulations matching MERS-CoV sequence clusters is shown on the right. Darker shade of grey indicates bins falling within the 95% percentiles. Monte Carlo simulations indicate <inline-formula><mml:math id="inf19"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> for MERS-CoV in humans is likely to be below 1.0, with numbers of zoonotic transmissions numbering in the hundreds.</p></caption><graphic xlink:href="elife-31257-fig3"></graphic><p content-type="supplemental-figure"><fig id="fig3s1" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.017</object-id><label>Figure 3—figure supplement 1.</label><caption><title>Monte Carlo simulations of human transmission clusters.</title><p>From top to bottom each row corresponds to departures from completely random sequencing efforts with respect to case cluster size (bias parameter = 1.0) to sequencing increasingly biased towards capturing large case clusters (bias = 2.0, bias = 3.0). Leftmost scatter plots show the distribution of individual Monte Carlo simulation sequence cluster size statistics (mean and skewness) coloured by the <inline-formula><mml:math id="inf20"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> value used for the simulation. The dotted rectangle identifies the 95% highest posterior density bounds for sequence cluster size mean and skewness observed for empirical MERS-CoV data. The distribution of <inline-formula><mml:math id="inf21"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> values matching empirical data are shown in the middle, on the same <inline-formula><mml:math id="inf22"><mml:mi>y</mml:mi></mml:math></inline-formula>-axis across all levels of the bias parameter. Under unbiased sequencing (bias = 1.0) only 0.45% of simulations fit our phylogenetic observations, while 1.79% and 1.67% of simulations fit for bias levels of 2.0 and 3.0, respectively. Correspondingly, we estimate 11.6% support for a model with bias level 1.0, 45.7% support for a model with bias level 2.0, and 42.7% support for a model with bias level 3.0. Bins falling inside the 95% percentiles are coloured by <inline-formula><mml:math id="inf23"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula>, as in the leftmost scatter plot. While the 95% percentiles for <inline-formula><mml:math id="inf24"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> values are close to 1.0 (0.71–0.98) for the unbiased sequencing simulation (i.e. uniform sequencing efforts, in which every case is equally likely to be sequenced), we also note that increasing levels of bias are considerably more to likely to generate MERS-CoV-like sequence clusters. The distribution of total number of introductions associated with simulations matching MERS-CoV sequence clusters is shown in the plots on the right, on the same <inline-formula><mml:math id="inf25"><mml:mi>y</mml:mi></mml:math></inline-formula>-axis across all levels of bias. Darker shade of grey indicates bins falling within the 95% percentiles. The median number of cross-species introductions observed in simulations matching empirical data without bias are 346 (95% percentiles 262–439). These numbers jump up to 568 (95% percentiles 430–727) for bias = 2.0 and 656 (95% percentiles 488–853) for bias = 3.0 simulations. Model averaging would suggest plausible numbers of introductions between 311 and 811.</p></caption><graphic xlink:href="elife-31257-fig3-figsupp1"></graphic></fig></p><p content-type="supplemental-figure"><fig id="fig3s2" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.018</object-id><label>Figure 3—figure supplement 2.</label><caption><title>Monte Carlo simulation schematic.</title><p>Case clusters are simulated according to <xref ref-type="disp-formula" rid="equ2">Equation 1</xref> until an outbreak size of 2000 cases is reached. We sample 174 cases from each simulation to represent sequencing of human MERS cases. ‘Sequencing’ is carried out by using multivariate hypergeometric sampling, representing sampling cases without replacement to be sequenced. Sequencing simulations take place at three levels of bias: 1.0, where every case is equally likely to be sequenced, and 2.0 and 3.0, where cases from larger clusters are increasingly more likely to be sequenced. The distribution of simulated sequence clusters is summarised by its mean, median and standard deviation. A simulation is considered to match if the mean, median and standard deviation of its sequence cluster sizes falls within the 95% highest posterior density interval of observed MERS-CoV sequence clusters. <inline-formula><mml:math id="inf26"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> values that ultimately generate data matching empirical observations, as well as associated numbers of ‘introductions’ are retained as estimates. These estimates are summarised in <xref ref-type="fig" rid="fig3">Figure 3</xref>.</p></caption><graphic xlink:href="elife-31257-fig3-figsupp2"></graphic></fig></p><p content-type="supplemental-figure"><fig id="fig3s3" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.019</object-id><label>Figure 3—figure supplement 3.</label><caption><title>Results of Monte Carlo simulations with vast underestimation of cases.</title><p>The plot is identical to <xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1</xref>, but instead of 2000 cases, simulations were run with 4000 cases. With more unobserved cases the R<inline-formula><mml:math id="inf27"><mml:msub><mml:mi></mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> values matching observed MERS-CoV sequence clusters can only be smaller, with a corresponding increase in numbers of zoonotic transmissions. However, the numbers of simulations that match MERS-CoV data go down as well.</p></caption><graphic xlink:href="elife-31257-fig3-figsupp3"></graphic></fig></p><p content-type="supplemental-figure"><fig id="fig3s4" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.020</object-id><label>Figure 3—figure supplement 4.</label><caption><title>Boxplots of matching simulated case and sequence cluster distributions.</title><p>Boxplots indicate frequency of case (blue, top) and sequence (red, bottom) cluster sizes across simulations at different bias levels, marginalised across <inline-formula><mml:math id="inf28"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> values. Outliers are shown with transparency, medians are indicated with thick black lines. Case clusters exhibit a strong skew with large numbers of singleton introductions and a substantial tail at higher levels of bias.</p></caption><graphic xlink:href="elife-31257-fig3-figsupp4"></graphic></fig></p><p content-type="supplemental-figure"><fig id="fig3s5" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.021</object-id><label>Figure 3—figure supplement 5.</label><caption><title>Quantile-quantile (Q-Q) plot of empirical and simulated sequence cluster sizes.</title><p>Density of sequence cluster size percentiles (1 st–99th, calculated across a grid of 50 values) calculated for random states from the posterior distribution (<inline-formula><mml:math id="inf29"><mml:mi>x</mml:mi></mml:math></inline-formula>-axis) and matching simulations (<inline-formula><mml:math id="inf30"><mml:mi>y</mml:mi></mml:math></inline-formula>-axis). Most values fall on the one-to-one line, with a heavier tail in mid-sized sequence clusters in empirical data, manifesting as a greater density of points below the one-to-one line in the middle.</p></caption><graphic xlink:href="elife-31257-fig3-figsupp5"></graphic></fig></p><p content-type="supplemental-figure"><fig id="fig3s6" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.022</object-id><label>Figure 3—figure supplement 6.</label><caption><title>Numbers of epidemiological simulations conforming to empirical observations.</title><p>Numbers indicate the total number of epidemiological simulations under each combination of bias and dispersion parameter <inline-formula><mml:math id="inf31"><mml:mi>ω</mml:mi></mml:math></inline-formula> that result in MERS-CoV-like sequence cluster sizes. More simulations match observations with bias <inline-formula><mml:math id="inf32"><mml:mrow><mml:mi></mml:mi><mml:mo>></mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="inf33"><mml:mrow><mml:mi>ω</mml:mi><mml:mo>≈</mml:mo><mml:mn>0.1</mml:mn></mml:mrow></mml:math></inline-formula>.</p></caption><graphic xlink:href="elife-31257-fig3-figsupp6"></graphic></fig></p></fig><p>We find that observed phylogenetic patterns of sequence clustering strongly support <inline-formula><mml:math id="inf34"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> below 1.0 (middle panel in <xref ref-type="fig" rid="fig3">Figure 3</xref>). Mean <inline-formula><mml:math id="inf35"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> value observed in matching simulations is 0.72 (95% percentiles 0.57–0.90), suggesting the inability of the virus to sustain transmission in humans. Lower values for <inline-formula><mml:math id="inf36"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> in turn suggest relatively large numbers of zoonotic transfers of viruses into humans (right-hand panel in <xref ref-type="fig" rid="fig3">Figure 3</xref>). Median number of cross-species introductions observed in matching simulations is 592 (95% percentiles 311–811). Our results suggest a large number of unobserved MERS primary cases. Given this, we also performed simulations where the total number of cases is doubled to 4000 to explore the impact of dramatic underestimation of MERS cases. In these analyses, <inline-formula><mml:math id="inf37"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> values tend to decrease even further as numbers of introductions go up, although very few simulations match currently observed MERS-CoV sequence data (<xref ref-type="fig" rid="fig3s3">Figure 3—figure supplement 3</xref>).</p><p>Overall, our analyses indicate that MERS-CoV is poorly suited for human-to-human transmission, with an estimated <inline-formula><mml:math id="inf38"><mml:mrow><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub><mml:mo><</mml:mo><mml:mn>0.90</mml:mn></mml:mrow></mml:math></inline-formula> and sequence sampling likely to be biased towards large hospital outbreaks (<xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1</xref>). All matching simulations exhibit highly skewed distributions of case cluster sizes with long tails (<xref ref-type="fig" rid="fig3s4">Figure 3—figure supplement 4</xref>), which is qualitatively similar to the results of (<xref rid="bib18" ref-type="bibr">Cauchemez et al., 2016</xref>). We find that simulated sequence cluster sizes resemble observed sequence cluster sizes in the posterior distribution, with a slight reduction in mid-sized clusters in simulated data (<xref ref-type="fig" rid="fig3s5">Figure 3—figure supplement 5</xref>). Given these findings, and the fact that large outbreaks of MERS occurred in hospitals, the combination of frequent spillover of MERS-CoV into humans and occasional outbreak amplification via poor hygiene practices (<xref rid="bib7" ref-type="bibr">Assiri et al., 2013b</xref>; <xref rid="bib19" ref-type="bibr">Chen et al., 2017</xref>) appear sufficient to explain observed epidemiological patterns of MERS-CoV.</p></sec><sec id="s2-4"><title>Recombination shapes MERS-CoV diversity</title><p>Recombination has been shown to occur in all genera of coronaviruses, including MERS-CoV (<xref rid="bib56" ref-type="bibr">Lai et al., 1985</xref>; <xref rid="bib65" ref-type="bibr">Makino et al., 1986</xref>; <xref rid="bib50" ref-type="bibr">Keck et al., 1988</xref>; <xref rid="bib54" ref-type="bibr">Kottier et al., 1995</xref>; <xref rid="bib44" ref-type="bibr">Herrewegh et al., 1998</xref>). In order to quantify the degree to recombination has shaped MERS-CoV genetic diversity, we used two recombination detection approaches across partitions of taxa corresponding to inferred MERS-CoV clades. Both methods rely on sampling parental and recombinant alleles within the alignment, although each quantifies different signals of recombination. One hallmark of recombination is the ability to carry alleles derived via mutation from one lineage to another, which appear as repeated mutations taking place in the recipient lineage, somewhere else in the tree. The PHI (pairwise homoplasy index) test quantifies the appearance of these excessive repeat mutations (homoplasies) within an alignment (<xref rid="bib16" ref-type="bibr">Bruen et al., 2006</xref>). Another hallmark of recombination is clustering of alleles along the genome, due to how template switching, the primary mechanism of recombination in RNA viruses, occurs. 3Seq relies on the clustering of nucleotide similarities along the genome between sequence triplets – two potential parent-donors and one candidate offspring-recipient sequences (<xref rid="bib13" ref-type="bibr">Boni et al., 2007</xref>).</p><p>Both tests can give spurious results in cases of extreme rate heterogeneity and sampling over time (<xref rid="bib31" ref-type="bibr">Dudas and Rambaut, 2016</xref>), but both tests have not been reported to fail simultaneously. PHI and 3Seq methods consistently identify most of the apparent ‘backbone’ of the MERS-CoV phylogeny as encompassing sequences with evidence of recombination (<xref ref-type="fig" rid="fig4s1">Figure 4—figure supplement 1</xref>). Neither method can identify where in the tree recombination occurred, but each full asterisk in <xref ref-type="fig" rid="fig4s1">Figure 4—figure supplement 1</xref> should be interpreted as the minimum partition of data that still captures both donor and recipient alleles involved in a recombination event. This suggests a non-negligible contribution of recombination in shaping existing MERS-CoV diversity. As done previously (<xref rid="bib31" ref-type="bibr">Dudas and Rambaut, 2016</xref>), we show large numbers of homoplasies in MERS-CoV data (<xref ref-type="fig" rid="fig4s2">Figure 4—figure supplement 2</xref>) with some evidence of genomic clustering of such alleles. These results are consistent with high incidence of MERS-CoV in camels (<xref rid="bib70" ref-type="bibr">Müller et al., 2014</xref>; <xref rid="bib21" ref-type="bibr">Corman et al., 2014</xref>; <xref rid="bib20" ref-type="bibr">Chu et al., 2014</xref>; <xref rid="bib83" ref-type="bibr">Reusken et al., 2014</xref>; <xref rid="bib3" ref-type="bibr">Ali et al., 2017</xref>), allowing for co-infection with distinct genotypes and thus recombination to occur (<xref rid="bib84" ref-type="bibr">Sabir et al., 2016</xref>).</p><p>Owing to these findings, we performed a sensitivity analysis in which we partitioned the MERS-CoV genome into two fragments and identified human outbreak clusters within each fragment. We find strong similarity in the grouping of human cases into outbreak clusters between fragments (<xref ref-type="fig" rid="fig4">Figure 4A</xref>). Between the two trees in <xref ref-type="fig" rid="fig4">Figure 4B</xref> four (out of 54) ‘human’ clades are expanded where either singleton introductions or two-taxon clades in fragment 2 join other clades in fragment 1. For the reverse comparison, there are five ‘human’ clades (out of 53) in fragment 2 that are expanded. All such clades have low divergence (<xref ref-type="fig" rid="fig4">Figure 4B</xref>) and thus incongruences in human clades are more likely to be caused by differences in deme assignment rather than actual recombination. And while we observe evidence of distinct phylogenetic trees from different parts of the MERS-CoV genome (<xref ref-type="fig" rid="fig4">Figure 4B</xref>), human clades are minimally affected and large portions of the posterior probability density in both parts of the genome are concentrated in shared clades (<xref ref-type="fig" rid="fig4s3">Figure 4—figure supplement 3</xref>). Additionally, we observe the same source-sink dynamics between camel and human populations in trees constructed from separate genomic fragments as were observed in the original full genome tree (<xref ref-type="fig" rid="fig1">Figures 1</xref> and <xref ref-type="fig" rid="fig4">4B</xref>).</p><fig id="fig4" position="float" orientation="portrait"><object-id pub-id-type="doi">10.7554/eLife.31257.023</object-id><label>Figure 4.</label><caption><title>Recombinant features of MERS-CoV phylogenies.</title><p>(<bold>A</bold>) Marginal posterior probabilities of taxa collected from humans belonging to the same clade in phylogenies derived from different parts of the genome. Taxa are ordered according to phylogeny of fragment 2 (genome positions 21001 to 29364) reduced to just the human tips and is displayed on the left. Human clusters are largely well-supported as monophyletic and consistent across trees of both genomic fragments. (<bold>B</bold>) Tanglegram connecting the same taxa between a phylogeny derived from fragment 1 (left, genome positions 1 to 21000) and fragment 2 (right, genome positions 21001 to 29364), reduced to just the human tips and branches with posterior probability <inline-formula><mml:math id="inf39"><mml:mrow><mml:mi></mml:mi><mml:mo><</mml:mo><mml:mn>0.1</mml:mn></mml:mrow></mml:math></inline-formula> collapsed. Human clusters exhibit limited diversity and corresponding low levels of incongruence within an introduction cluster.</p><p><supplementary-material content-type="local-data" id="fig4sdata1"><object-id pub-id-type="doi">10.7554/eLife.31257.027</object-id><label>Figure 4—source data 1.</label><caption><title>XML to run structured coalescent analysis on bisected alignment with output files.</title></caption><media mime-subtype="zip" mimetype="application" xlink:href="elife-31257-fig4-data1.zip" orientation="portrait" id="d35e1288" position="anchor"></media></supplementary-material></p><p><supplementary-material content-type="local-data" id="fig4sdata2"><object-id pub-id-type="doi">10.7554/eLife.31257.028</object-id><label>Figure 4—source data 2.</label><caption><title>Output from PHI and 3Seq recombination analyses.</title></caption><media mime-subtype="zip" mimetype="application" xlink:href="elife-31257-fig4-data2.zip" orientation="portrait" id="d35e1298" position="anchor"></media></supplementary-material></p><p><supplementary-material content-type="local-data" id="fig4sdata3"><object-id pub-id-type="doi">10.7554/eLife.31257.029</object-id><label>Figure 4—source data 3.</label><caption><title>Output from ClonalFrameML analysis.</title></caption><media mime-subtype="zip" mimetype="application" xlink:href="elife-31257-fig4-data3.zip" orientation="portrait" id="d35e1308" position="anchor"></media></supplementary-material></p></caption><graphic xlink:href="elife-31257-fig4"></graphic><p content-type="supplemental-figure"><fig id="fig4s1" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.024</object-id><label>Figure 4—figure supplement 1.</label><caption><title>Tests of recombination across MERS-CoV clades.</title><p>Maximum clade credibility tree of MERS-CoV genomes annotated with results of two recombination detection tests (PHI and 3Seq) applied to descendent sequences of each clade. Both tests identify large portions of existing sequence data as containing signals of recombination. Note that markings do not indicate where recombinations have occurred on the tree, merely the minimum distance in sequence/time space between recombining lineages.</p></caption><graphic xlink:href="elife-31257-fig4-figsupp1"></graphic></fig></p><p content-type="supplemental-figure"><fig id="fig4s2" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.025</object-id><label>Figure 4—figure supplement 2.</label><caption><title>MERS-CoV genomes exhibit high numbers of non-clonal loci.</title><p>Ancestral state reconstruction (right) identifies a large number of sites in which mutations have occurred more than once in the tree (homoplasies, orange) or are reversions (red) from a state arising in an ancestor. Mutations that apparently only occur once in the tree (synapomorphies) are shown in grey. The maximum likelihood phylogeny on the left is coloured by whether sequences were sampled in humans (blue) or camels (orange).</p></caption><graphic xlink:href="elife-31257-fig4-figsupp2"></graphic></fig></p><p content-type="supplemental-figure"><fig id="fig4s3" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.026</object-id><label>Figure 4—figure supplement 3.</label><caption><title>Human clade sharing between genomic fragments 1 and 2.</title><p>Central scatter plot shows the posterior probability of human clades shared between genomic fragments 1 and 2, in their respective trees. Left and bottom scatter plots track the posterior probability of human clades only observed in fragment 2 (left) or fragment 1 (bottom). The cumulative probability of human clades present in either tree are tracked by plots on the right (fragment 2) and top (fragment 1). Most of the probability mass is concentrated within human clades that are present in trees of both genomic fragment 1 and 2 (0.9701 and 0.9474 of all human clades across posteriors, respectively).</p></caption><graphic xlink:href="elife-31257-fig4-figsupp3"></graphic></fig></p></fig><p>Observed departures from strictly clonal evolution suggest that while recombination is an issue for inferring MERS-CoV phylogenies, its effect on the human side of MERS outbreaks is minimal, as expected if humans represent a transient host with little opportunity for co-infection. MERS-CoV evolution on the reservoir side is complicated by recombination, although is nonetheless still largely amenable to phylogenetic methods. Amongst other parameters of interest, recombination is expected to interfere with molecular clocks, where transferred genomic regions can give the impression of branches undergoing rapid evolution, or branches where recombination results in reversions appearing to evolve slow. In addition to its potential to influence tree topology, recombination in molecular sequence data is an erratic force with unpredictable effects. We suspect that the effects of recombination in MERS-CoV data are reigned in by a relatively small effective population size of the virus in Saudi Arabia (see next section) where haplotypes are fixed or nearly fixed, thus preventing an accumulation of genetic diversity that would then be reshuffled via recombination. Nevertheless the evolutionary rate of the virus appears to fall firmly within the expected range for RNA viruses: regression of nucleotide differences to Jordan-N3/2012 genome against sequence collection dates yields a rate of <inline-formula><mml:math id="inf40"><mml:mrow><mml:mn>4.59</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mn>10</mml:mn><mml:mrow><mml:mo>-</mml:mo><mml:mn>4</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> subs/site/year, Bayesian structured coalescent estimate from primary analysis <inline-formula><mml:math id="inf41"><mml:mrow><mml:mn>9.57</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mn>10</mml:mn><mml:mrow><mml:mo>-</mml:mo><mml:mn>4</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> (95% HPDs: <inline-formula><mml:math id="inf42"><mml:mrow><mml:mn>8.28</mml:mn><mml:mo>-</mml:mo><mml:mrow><mml:mn>10.9</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mn>10</mml:mn><mml:mrow><mml:mo>-</mml:mo><mml:mn>4</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:mrow></mml:math></inline-formula>) subs/site/year.</p></sec><sec id="s2-5"><title>MERS-CoV shows population turnover in camels</title><p>Here, we attempt to investigate MERS-CoV demographic patterns in the camel reservoir. We supplement camel sequence data with a single earliest sequence from each human cluster, treating viral diversity present in humans as a sentinel sample of MERS-CoV diversity circulating in camels. This removes conflicting demographic signals sampled during human outbreaks, where densely sampled closely related sequences from humans could be misconstrued as evidence of demographic crash in the viral population.</p><p>Despite lack of convergence, neither of the two demographic reconstructions show evidence of fluctuations in the scaled effective population size (<inline-formula><mml:math id="inf43"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo></mml:mo><mml:mi>τ</mml:mi></mml:mrow></mml:math></inline-formula>) of MERS-CoV over time (<xref ref-type="fig" rid="fig5">Figure 5</xref>). We recover a similar demographic trajectory when estimating <inline-formula><mml:math id="inf44"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo></mml:mo><mml:mi>τ</mml:mi></mml:mrow></mml:math></inline-formula> over time with a skygrid tree prior across the genome split into ten fragments with independent phylogenetic trees to account for confounding effects of recombination (<xref ref-type="fig" rid="fig5s1">Figure 5—figure supplement 1</xref>). However, we do note that coalescence rate estimates are high relative to the sampling time period, with a mean estimate of <inline-formula><mml:math id="inf45"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo></mml:mo><mml:mi>τ</mml:mi></mml:mrow></mml:math></inline-formula> at 3.49 years (95% HPD: 2.71–4.38), and consequently MERS-CoV phylogeny resembles a ladder, as often seen in human influenza A virus phylogenies (<xref rid="bib11" ref-type="bibr">Bedford et al., 2011</xref>).</p><fig id="fig5" position="float" orientation="portrait"><object-id pub-id-type="doi">10.7554/eLife.31257.030</object-id><label>Figure 5.</label><caption><title>Demographic history of MERS-CoV in Arabian peninsula camels.</title><p>Demographic history of MERS-CoV in camels, as inferred via a skygrid coalescent tree prior (<xref rid="bib36" ref-type="bibr">Gill et al., 2013</xref>). Three skygrid reconstructions are shown, red and orange for each of the stationary distributions reached by MCMC with the whole genome and a black one where the genome was split into ten partitions. Shaded interval indicates the 95% highest posterior density interval for the product of generation time and effective population size, <inline-formula><mml:math id="inf46"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo></mml:mo><mml:mi>τ</mml:mi></mml:mrow></mml:math></inline-formula>. Midline tracks the inferred median of <inline-formula><mml:math id="inf47"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo></mml:mo><mml:mi>τ</mml:mi></mml:mrow></mml:math></inline-formula>.</p><p><supplementary-material content-type="local-data" id="fig5sdata1"><object-id pub-id-type="doi">10.7554/eLife.31257.032</object-id><label>Figure 5—source data 1.</label><caption><title>XML to run skygrid analysis on camel-like sequence data and output files.</title></caption><media mime-subtype="zip" mimetype="application" xlink:href="elife-31257-fig5-data1.zip" orientation="portrait" id="d35e1503" position="anchor"></media></supplementary-material></p></caption><graphic xlink:href="elife-31257-fig5"></graphic><p content-type="supplemental-figure"><fig id="fig5s1" specific-use="child-fig" orientation="portrait" position="anchor"><object-id pub-id-type="doi">10.7554/eLife.31257.031</object-id><label>Figure 5—figure supplement 1.</label><caption><title>Skygrid comparison between whole and fragmented genomes.</title><p>Inferred median <inline-formula><mml:math id="inf48"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo></mml:mo><mml:mi>τ</mml:mi></mml:mrow></mml:math></inline-formula> recovered using a skygrid tree prior on whole genome (bottom) and ten genomic fragments with independent trees (left), coloured by time. Dotted line indicates the one-to-one line.</p></caption><graphic xlink:href="elife-31257-fig5-figsupp1"></graphic></fig></p></fig><p>This empirically estimated effectived population can be compared to the expected effective population size in a simple epidemiological model. At endemic equilibrium, we expect scaled effective population size <inline-formula><mml:math id="inf49"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo></mml:mo><mml:mi>τ</mml:mi></mml:mrow></mml:math></inline-formula> to follow <inline-formula><mml:math id="inf50"><mml:mrow><mml:mrow><mml:mpadded width="+1.7pt"><mml:mi>I</mml:mi></mml:mpadded><mml:mo>/</mml:mo><mml:mn> 2</mml:mn></mml:mrow><mml:mo></mml:mo><mml:mi>β</mml:mi></mml:mrow></mml:math></inline-formula>, where <inline-formula><mml:math id="inf51"><mml:mi>β</mml:mi></mml:math></inline-formula> is the equilibrium rate of transmission and <inline-formula><mml:math id="inf52"><mml:mi>I</mml:mi></mml:math></inline-formula> is the equilibrium number of infecteds (<xref rid="bib35" ref-type="bibr">Frost and Volz, 2010</xref>). We assume that <inline-formula><mml:math id="inf53"><mml:mi>β</mml:mi></mml:math></inline-formula> is constant and is equal to the rate of recovery. Given a 20 day duration of infection in camels (<xref rid="bib2" ref-type="bibr">Adney et al., 2014</xref>), we arrive at <inline-formula><mml:math id="inf54"><mml:mrow><mml:mi>β</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mn>365</mml:mn><mml:mo>/</mml:mo><mml:mn>20</mml:mn></mml:mrow><mml:mo>=</mml:mo><mml:mn>18.25</mml:mn></mml:mrow></mml:math></inline-formula> infections per year. Given extremely high seroprevalence estimates within camels in Saudi Arabia (<xref rid="bib70" ref-type="bibr">Müller et al., 2014</xref>; <xref rid="bib21" ref-type="bibr">Corman et al., 2014</xref>; <xref rid="bib20" ref-type="bibr">Chu et al., 2014</xref>; <xref rid="bib82" ref-type="bibr">Reusken et al., 2013</xref>; <xref rid="bib83" ref-type="bibr">Reusken et al., 2014</xref>), we expect camels to usually be infected within their first year of life. Therefore, we can estimate the rough number of camel infections per year as the number of calves produced each year. We find there are 830,000 camels in Saudi Arabia (<xref rid="bib1" ref-type="bibr">Abdallah and Faye, 2013</xref>) and that female camels in Saudi Arabia have an average fecundity of 45% (<xref rid="bib1" ref-type="bibr">Abdallah and Faye, 2013</xref>). Thus, we expect <inline-formula><mml:math id="inf55"><mml:mrow><mml:mrow><mml:mn>830 000</mml:mn><mml:mo>×</mml:mo><mml:mn>0.50</mml:mn><mml:mo>×</mml:mo><mml:mn>0.45</mml:mn></mml:mrow><mml:mo>=</mml:mo><mml:mn>186 750</mml:mn></mml:mrow></mml:math></inline-formula> new calves produced yearly and correspondingly 186,750 new infections every year, which spread over 20 day intervals gives an average prevalence of <inline-formula><mml:math id="inf56"><mml:mrow><mml:mi>I</mml:mi><mml:mo>=</mml:mo><mml:mn>10 233</mml:mn></mml:mrow></mml:math></inline-formula> infections. This results in an expected scaled effective population size <inline-formula><mml:math id="inf57"><mml:mrow><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo></mml:mo><mml:mi>τ</mml:mi></mml:mrow><mml:mo>=</mml:mo><mml:mn>280.4</mml:mn></mml:mrow></mml:math></inline-formula> years.</p><p>Comparing expected <inline-formula><mml:math id="inf58"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo></mml:mo><mml:mi>τ</mml:mi></mml:mrow></mml:math></inline-formula> to empirical <inline-formula><mml:math id="inf59"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo></mml:mo><mml:mi>τ</mml:mi></mml:mrow></mml:math></inline-formula> we arrive at a ratio of 80.3 (64.0–103.5). This is less than the equivalent ratio for human measles virus (<xref rid="bib11" ref-type="bibr">Bedford et al., 2011</xref>) and is in line with the expectation from neutral evolutionary dynamics plus some degree of transmission heterogeneity (<xref rid="bib90" ref-type="bibr">Volz et al., 2013</xref>) and seasonal troughs in prevalence. Thus, we believe that the ladder-like appearance of the MERS-CoV tree can likely be explained by entirely demographic factors.</p></sec></sec><sec sec-type="discussion" id="s3"><title>Discussion</title><sec id="s3-1"><title>MERS-CoV epidemiology</title><p>In this study we aimed to understand the drivers of MERS coronavirus transmission in humans and what role the camel reservoir plays in perpetuating the epidemic in the Arabian peninsula by using sequence data collected from both hosts (174 from humans and 100 from camels). We showed that currently existing models of population structure (<xref rid="bib89" ref-type="bibr">Vaughan et al., 2014</xref>) can identify distinct demographic modes in MERS-CoV genomic data, where viruses continuously circulating in camels repeatedly jump into humans and cause small outbreaks doomed to extinction (<xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1</xref>). This inference succeeds under different choices of priors for unknown demographic parameters (<xref ref-type="fig" rid="fig1s2">Figure 1—figure supplement 2</xref>) and in the presence of strong biases in sequence sampling schemes (<xref ref-type="fig" rid="fig3">Figure 3</xref>). When rapid coalescence in the human deme is not allowed (<xref ref-type="fig" rid="fig1s4">Figure 1—figure supplement 4</xref>) structured coalescent inference loses power and ancestral state reconstruction is nearly identical to that of discrete trait analysis (<xref ref-type="fig" rid="fig1s3">Figure 1—figure supplement 3</xref>). When allowed different deme-specific population sizes, the structured coalescent model succeeds because a large proportion of human sequences fall into tightly connected clusters, which informs a low estimate for the population size of the human deme. This in turn informs the inferred state of long ancestral branches in the phylogeny, that is, because these long branches are not immediately coalescing, they are most likely in camels.</p><p>From sequence data, we identify at least 50 zoonotic introductions of MERS-CoV into humans from the reservoir (<xref ref-type="fig" rid="fig1">Figure 1</xref>), from which we extrapolate that hundreds more such introductions must have taken place (<xref ref-type="fig" rid="fig3">Figure 3</xref>). Although we recover migration rates from our model (<xref ref-type="fig" rid="fig1s2">Figure 1—figure supplement 2</xref>), these only pertain to sequences and in no way reflect the epidemiologically relevant <italic>per capita</italic> rates of zoonotic spillover events. We also looked at potential seasonality in MERS-CoV spillover into humans. Our analyses indicated a period of three months where the odds of a sequenced spillover event are increased, with timing consistent with an enzootic amongst camel calves (<xref ref-type="fig" rid="fig2">Figure 2</xref>). As a result of our identification of large and asymmetric flow of viral lineages into humans we also find that the basic reproduction number for MERS-CoV in humans is well below the epidemic threshold (<xref ref-type="fig" rid="fig3">Figure 3</xref>). Having said that, there are highly customisable coalescent methods available that extend the methods used here to accommodate time varying migration rates and population sizes, integrate alternative sources of information and fit to stochastic nonlinear models (<xref rid="bib79" ref-type="bibr">Rasmussen et al., 2014</xref>), which would be more appropriate for MERS-CoV. Some distinct aspects of MERS-CoV epidemiology could not be captured in our methodology, such as hospital outbreaks where <inline-formula><mml:math id="inf60"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> is expected to be consistently closer to 1.0 compared to community transmission of MERS-CoV. Outside of coalescent-based models, there are population structure models that explicitly relate epidemiological parameters to the branching process observed in sequence data (<xref rid="bib55" ref-type="bibr">Kühnert et al., 2016</xref>), but often rely on specifying numerous informative priors and can suffer from MCMC convergence issues.</p><p>Strong population structure in viruses often arises through limited gene flow, either due to geography (<xref rid="bib30" ref-type="bibr">Dudas et al., 2017</xref>), ecology (<xref rid="bib86" ref-type="bibr">Smith et al., 2009</xref>) or evolutionary forces (<xref rid="bib87" ref-type="bibr">Turner et al., 2005</xref>; <xref rid="bib29" ref-type="bibr">Dudas et al., 2015</xref>). On a smaller scale, population structure can unveil important details about transmission patterns, such as identifying reservoirs and understanding spillover trends and risk, much as we have done here. When properly understood naturally arising barriers to gene flow can be exploited for more efficient disease control and prevention, as well as risk management.</p></sec><sec id="s3-2"><title>Transmissibility differences between zoonoses and pandemics</title><p>Severe acute respiratory syndrome (SARS) coronavirus, a Betacoronavirus like MERS-CoV, caused a serious epidemic in humans in 2003, with over 8000 cases and nearly 800 deaths. Since MERS-CoV was also able to cause significant pathogenicity in the human host it was inevitable that parallels would be drawn between MERS-CoV and SARS-CoV at the time of MERS discovery in 2012. Although we describe the epidemiology of MERS-CoV from sequence data, indications that MERS-CoV has poor capacity to spread human-to-human existed prior to any sequence data. SARS-CoV swept through the world in a short period of time, but MERS cases trickled slowly and were restricted to the Arabian Peninsula or resulted in self-limiting outbreaks outside of the region, a pattern strongly indicative of repeat zoonotic spillover. Infectious disease surveillance and control measures remain limited, so much like the SARS epidemic in 2003 or the H1N1 pandemic in 2009, zoonotic pathogens with <inline-formula><mml:math id="inf61"><mml:mrow><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub><mml:mo>></mml:mo><mml:mn>1.0</mml:mn></mml:mrow></mml:math></inline-formula> are probably going to be discovered after spreading beyond the original location of spillover. Even though our results show that MERS-CoV does not appear to present an imminent global threat, we would like to highlight that its epidemiology is nonetheless concerning.</p><p>Pathogens <italic>Bacillus anthracis</italic>, Andes hantavirus (<xref rid="bib66" ref-type="bibr">Martinez et al., 2005</xref>), monkeypox (<xref rid="bib80" ref-type="bibr">Reed et al., 2004</xref>) and influenza A are able to jump species barriers but only influenza A viruses have historically resulted in pandemics (<xref rid="bib60" ref-type="bibr">Lipsitch et al., 2016</xref>). MERS-CoV may join the list of pathogens able to jump species barriers but not spread efficiently in the new host. Since its emergence in 2012, MERS-CoV has caused self-limiting outbreaks in humans with no evidence of worsening outbreaks over time. However, sustained evolution of the virus in the reservoir and continued flow of viral lineages into humans provides the substrate for a more transmissible variant of MERS-CoV to possibly emerge. Previous modelling studies (<xref rid="bib5" ref-type="bibr">Antia et al., 2003</xref>; <xref rid="bib74" ref-type="bibr">Park et al., 2013</xref>) suggest a positive relationship between initial <inline-formula><mml:math id="inf62"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> in the human host and probability of evolutionary emergence of a novel strain which passes the supercritical threshold of <inline-formula><mml:math id="inf63"><mml:mrow><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub><mml:mo>></mml:mo><mml:mn>1.0</mml:mn></mml:mrow></mml:math></inline-formula>. This leaves MERS-CoV in a precarious position; on one hand its current <inline-formula><mml:math id="inf64"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> of <inline-formula><mml:math id="inf65"><mml:mo>∼</mml:mo></mml:math></inline-formula>0.7 is certainly less than 1, but its proximity to the supercritical threshold raises alarm. With very little known about the fitness landscape or adaptive potential of MERS-CoV, it is incredibly challenging to predict the likelihood of the emergence more transmissible variants. In light of these difficulties, we encourage continued genomic surveillance of MERS-CoV in the camel reservoir and from sporadic human cases to rapidly identify a supercritical variant, if one does emerge.</p></sec></sec><sec id="s4"><title>Materials and methods</title><sec id="s4-1"><title>Sequence data</title><p>All MERS-CoV sequences were downloaded from GenBank and accession numbers are given in <xref ref-type="supplementary-material" rid="supp1">Supplementary file 1</xref> (<xref rid="bib8" ref-type="bibr">Assiri et al., 2016a</xref>, <xref rid="bib9" ref-type="bibr">2016b</xref>; <xref rid="bib10" ref-type="bibr">Azhar et al., 2014</xref>; <xref rid="bib88" ref-type="bibr">van Boheemen et al., 2012</xref>; <xref rid="bib15" ref-type="bibr">Briese et al., 2014</xref>; <xref rid="bib20" ref-type="bibr">Chu et al., 2014</xref>; <xref rid="bib22" ref-type="bibr">Cotten et al., 2013</xref>, <xref rid="bib23" ref-type="bibr">2014</xref>; <xref rid="bib26" ref-type="bibr">Drosten et al., 2013</xref>, <xref rid="bib25" ref-type="bibr">2015</xref>; <xref rid="bib33" ref-type="bibr">Fagbo et al., 2015</xref>; <xref rid="bib40" ref-type="bibr">Haagmans et al., 2014</xref>; <xref rid="bib43" ref-type="bibr">Hemida et al., 2014</xref>; <xref rid="bib46" ref-type="bibr">Hunter et al., 2016</xref>; <xref rid="bib47" ref-type="bibr">Kandeil et al., 2016</xref>; <xref rid="bib48" ref-type="bibr">Kapoor et al., 2014</xref>; <xref rid="bib52" ref-type="bibr">Kim et al., 2015</xref>, <xref rid="bib51" ref-type="bibr">2016</xref>; <xref rid="bib57" ref-type="bibr">Lamers et al., 2016</xref>; <xref rid="bib58" ref-type="bibr">Lau et al., 2016</xref>; <xref rid="bib63" ref-type="bibr">Lu et al., 2017</xref>; <xref rid="bib73" ref-type="bibr">Park et al., 2016a</xref>, <xref rid="bib75" ref-type="bibr">2016b</xref>; <xref rid="bib76" ref-type="bibr">Plipat et al., 2017</xref>; <xref rid="bib78" ref-type="bibr">Raj et al., 2014</xref>; <xref rid="bib84" ref-type="bibr">Sabir et al., 2016</xref>; <xref rid="bib85" ref-type="bibr">Seong et al., 2016</xref>; <xref rid="bib97" ref-type="bibr">Xie et al., 2015</xref>). Sequences without accessions were kindly shared by Ali M. Somily, Mazin Barry, Sarah S. Al Subaie, Abdulaziz A. BinSaeed, Fahad A. Alzamil, Waleed Zaher, Theeb Al Qahtani, Khaldoon Al Jerian, Scott J.N. McNabb, Imad A. Al-Jahdali, Ahmed M. Alotaibi, Nahid A. Batarfi, Matthew Cotten, Simon J. Watson, Spela Binter, and Paul Kellam prior to publication. Sequences available on GenBank but not associated with publications were shared by Meriadeg Ar Gouilh, Emad M. Elassal, Monica Galiano, Krista Queen and Ying Tao. Fragments of some strains submitted to GenBank as separate accessions were assembled into a single sequence. Only sequences covering at least 50% of MERS-CoV genome were kept, to facilitate later analyses where the alignment is split into two parts in order to account for effects of recombination (<xref rid="bib31" ref-type="bibr">Dudas and Rambaut, 2016</xref>). Sequences were annotated with available collection dates and hosts, designated as camel or human, aligned with MAFFT (<xref rid="bib49" ref-type="bibr">Katoh and Standley, 2013</xref>), and edited manually. Protein coding sequences were extracted and concatenated, reducing alignment length from 30,130 down to 29,364, which allowed for codon-partitioned substitution models to be used. The final dataset consisted of 174 genomes from human infections and 100 genomes from camel infections (<xref ref-type="supplementary-material" rid="supp1">Supplementary file 1</xref>).</p></sec><sec id="s4-2"><title>Phylogenetic analyses</title><sec id="s4-2-1"><title>Primary analysis, structured coalescent</title><p>For our primary analysis, the MultiTypeTree module (<xref rid="bib89" ref-type="bibr">Vaughan et al., 2014</xref>) of BEAST v2.4.3 (<xref rid="bib14" ref-type="bibr">Bouckaert et al., 2014</xref>) was used to specify a structured coalescent model with two demes – humans and camels. At time of writing structured population models are available in BEAST v2 (<xref rid="bib14" ref-type="bibr">Bouckaert et al., 2014</xref>) but not in BEAST v1 (<xref rid="bib28" ref-type="bibr">Drummond et al., 2012</xref>). We use the more computationally intensive MultiTypeTree module (<xref rid="bib89" ref-type="bibr">Vaughan et al., 2014</xref>) over approximate methods also available in BEAST v2, such as BASTA (<xref rid="bib24" ref-type="bibr">De Maio et al., 2015</xref>), MASCOT (<xref rid="bib69" ref-type="bibr">Mueller et al., 2017</xref>), and PhyDyn (<xref rid="bib91" ref-type="bibr">Volz, 2012</xref>). Structured coalescent model implemented in the MultiTypeTree module (<xref rid="bib89" ref-type="bibr">Vaughan et al., 2014</xref>) estimates four parameters: rate of coalescence in human viruses, rate of coalescence in camel viruses, rate of migration from the human deme to the camel deme and rate of migration from the camel deme to the human deme. Analyses were run on codon position partitioned data with two separate HKY+<inline-formula><mml:math id="inf66"><mml:msub><mml:mi mathvariant="normal">Γ</mml:mi><mml:mn>4</mml:mn></mml:msub></mml:math></inline-formula>(<xref rid="bib41" ref-type="bibr">Hasegawa et al., 1985</xref>; <xref rid="bib98" ref-type="bibr">Yang, 1994</xref>) nucleotide substitution models specified for codon positions 1 + 2 and 3. A relaxed molecular clock with branch rates drawn from a lognormal distribution (<xref rid="bib27" ref-type="bibr">Drummond et al., 2006</xref>) was used to infer the evolutionary rate from date calibrated tips. Default priors were used for all parameters except for migration rates between demes for which an exponential prior with mean 1.0 was used. All analyses were run for 200 million steps across ten independent Markov chains (MCMC runs) and states were sampled every 20,000 steps. Due to the complexity of multitype tree parameter space 50% of states from every analysis were discarded as burn-in, convergence assessed in Tracer v1.6 and states combined using LogCombiner distributed with BEAST v2.4.3 (<xref rid="bib14" ref-type="bibr">Bouckaert et al., 2014</xref>). Three chains out of ten did not converge and were discarded altogether. This left 70,000 states on which to base posterior inference. Posterior sets of typed (where migrating branches from structured coalescent are collapsed, and migration information is left as a switch in state between parent and descendant nodes) trees were summarised using TreeAnnotator v2.4.3 with the common ancestor heights option (<xref rid="bib42" ref-type="bibr">Heled and Bouckaert, 2013</xref>). A maximum likelihood phylogeny showing just the genetic relationships between MERS-CoV genomes from camels and humans was recovered using PhyML (<xref rid="bib39" ref-type="bibr">Guindon et al., 2003</xref>) under a HKY+<inline-formula><mml:math id="inf67"><mml:msub><mml:mi mathvariant="normal">Γ</mml:mi><mml:mn>4</mml:mn></mml:msub></mml:math></inline-formula>(<xref rid="bib41" ref-type="bibr">Hasegawa et al., 1985</xref>; <xref rid="bib98" ref-type="bibr">Yang, 1994</xref>) nucleotide substitution model and is shown in <xref ref-type="fig" rid="fig1s5">Figure 1—figure supplement 5</xref>.</p></sec><sec id="s4-2-2"><title>Control, structured coalescent with different prior</title><p>As a secondary analysis to test robustness to choice of prior, we set up an analysis where we increased the mean of the exponential distribution prior for migration rate to 10.0. All other parameters were identical to the primary analysis and as before 10 independent MCMC chains were run. In this case, two chains did not converge. This left 80,000 states on which to base posterior inference. Posterior sets of typed trees were summarised using TreeAnnotator v2.4.3 with the common ancestor heights option (<xref rid="bib42" ref-type="bibr">Heled and Bouckaert, 2013</xref>).</p></sec><sec id="s4-2-3"><title>Control, structured coalescent with equal deme sizes</title><p>To better understand where statistical power of the structured coalescent model lies we set up a tertiary analysis where a model was set up identically to the first structured coalescent analysis, but deme population sizes were enforced to have the same size. This analysis allowed us to differentiate whether statistical power in our analysis is coming from effective population size contrasts between demes or the backwards-in-time migration rate estimation. Five replicate chains were set up, two of which failed to converge after 200 million states. Combining the three converging runs left us with 15,000 trees sampled from the posterior distribution, which were summarised in TreeAnnotator v2.4.3 with the common ancestor heights option (<xref rid="bib42" ref-type="bibr">Heled and Bouckaert, 2013</xref>).</p></sec><sec id="s4-2-4"><title>Control, structured coalescent with more than one tree per genome</title><p>Due to concerns that recombination might affect our conclusions (<xref rid="bib31" ref-type="bibr">Dudas and Rambaut, 2016</xref>), as an additional secondary analysis, we also considered a scenario where alignments were split into two fragments (fragment 1 comprised of positions 1–21000, fragment 2 of positions 21000–29364), with independent clocks, trees and migration rates, but shared substitution models and deme population sizes. Fragment positions were chosen based on consistent identification of the region around nucleotide 21000 as a probable breakpoint by GARD (<xref rid="bib53" ref-type="bibr">Kosakovsky Pond et al., 2006</xref>) by previous studies into SARS and MERS coronaviruses (<xref rid="bib45" ref-type="bibr">Hon et al., 2008</xref>; <xref rid="bib31" ref-type="bibr">Dudas and Rambaut, 2016</xref>). All analyses were set to run for 200 million states, subsampling every 20,000 states. Chains not converging after 200 million states were discarded. 20% of the states were discarded as burn-in, convergence assessed with Tracer 1.6 and combined with LogCombiner. Three chains out of ten did not converge. This left 70,000 states on which to base posterior inference. Posterior sets of typed trees were summarised using TreeAnnotator v2.4.3 with the common ancestor heights option (<xref rid="bib42" ref-type="bibr">Heled and Bouckaert, 2013</xref>).</p></sec><sec id="s4-2-5"><title>Control, discrete trait analysis</title><p>A currently widely used approach to infer ancestral states in phylogenies relies on treating traits of interest (such as geography, host, <italic>etc.</italic>) as features evolving along a phylogeny as continuous time Markov chains with an arbitrary number of states (<xref rid="bib59" ref-type="bibr">Lemey et al., 2009</xref>). Unlike structured coalescent methods, such discrete trait approaches are independent from the tree (i.e. demographic) prior and thus unable to influence coalescence rates under different trait states. Such models have been used in the past to infer the number of MERS-CoV host jumps (<xref rid="bib100" ref-type="bibr">Zhang et al., 2016</xref>) with results contradicting other sources of information. In order to test how a discrete trait approach compares to the structured coalescent we used our 274 MERS-CoV genome data set in BEAST v2.4.3 (<xref rid="bib14" ref-type="bibr">Bouckaert et al., 2014</xref>) and specified identical codon-partitioned nucleotide substitution and molecular clock models to our structured coalescent analysis. To give the most comparable results, we used a constant population size coalescent model, as this is the demographic function for each deme in the structured coalescent model. Five replicate MCMC analyses were run for 200 million states, three of which converged onto the same posterior distribution. The converging chains were combined after removing 20 million states as burn-in to give a total of 27,000 trees drawn from the posterior distribution. These trees were then summarised using TreeAnnotator v2.4.5 with the common ancestor heights option (<xref rid="bib42" ref-type="bibr">Heled and Bouckaert, 2013</xref>).</p></sec><sec id="s4-2-6"><title>Introduction seasonality</title><p>We extracted the times of camel-to-human introductions from the posterior distribution of multitype trees. This distribution of introduction times was then discretised as follows: for sample <inline-formula><mml:math id="inf68"><mml:mrow><mml:mi>k</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>,</mml:mo><mml:mn>2</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:mi>L</mml:mi></mml:mrow></mml:mrow></mml:math></inline-formula> from the posterior, <inline-formula><mml:math id="inf69"><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mo></mml:mo><mml:mi>j</mml:mi><mml:mo></mml:mo><mml:mi>k</mml:mi></mml:mrow></mml:msub></mml:math></inline-formula> was <inline-formula><mml:math id="inf70"><mml:mn>1</mml:mn></mml:math></inline-formula> if there as an introduction in month <inline-formula><mml:math id="inf71"><mml:mi>i</mml:mi></mml:math></inline-formula> and year <inline-formula><mml:math id="inf72"><mml:mi>j</mml:mi></mml:math></inline-formula> and 0 otherwise. We model the sum of introductions at month <inline-formula><mml:math id="inf73"><mml:mi>i</mml:mi></mml:math></inline-formula> and year <inline-formula><mml:math id="inf74"><mml:mi>j</mml:mi></mml:math></inline-formula> across the posterior sample <inline-formula><mml:math id="inf75"><mml:mrow><mml:msub><mml:mi>Y</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mo></mml:mo><mml:mi>j</mml:mi></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mrow><mml:msubsup><mml:mo largeop="true" symmetric="true">∑</mml:mo><mml:mrow><mml:mi>k</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>L</mml:mi></mml:msubsup><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mo></mml:mo><mml:mi>j</mml:mi><mml:mo></mml:mo><mml:mi>k</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mrow></mml:math></inline-formula> with the hierarchical model:<disp-formula id="equ1"><mml:math id="m1"><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mrow><mml:mtable columnalign="right left right left right left right left right left right left" columnspacing="0em 2em 0em 2em 0em 2em 0em 2em 0em 2em 0em" displaystyle="true" rowspacing="3pt"><mml:mtr><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:msub><mml:mi>Y</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub></mml:mstyle></mml:mtd><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mo>∼</mml:mo><mml:mtext>Binomial</mml:mtext><mml:mo stretchy="false">(</mml:mo><mml:mi>L</mml:mi><mml:mo>,</mml:mo><mml:msub><mml:mi>θ</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:mstyle></mml:mtd><mml:mtd></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:msub><mml:mi>θ</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub></mml:mstyle></mml:mtd><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mo>=</mml:mo><mml:mrow><mml:mi mathvariant="normal">i</mml:mi><mml:mi mathvariant="normal">n</mml:mi><mml:mi mathvariant="normal">v</mml:mi><mml:mi mathvariant="normal">e</mml:mi><mml:mi mathvariant="normal">r</mml:mi><mml:mi mathvariant="normal">s</mml:mi><mml:mi mathvariant="normal">e</mml:mi><mml:mtext> </mml:mtext><mml:mi mathvariant="normal">l</mml:mi><mml:mi mathvariant="normal">o</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mi mathvariant="normal">i</mml:mi><mml:mi mathvariant="normal">t</mml:mi></mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mrow><mml:mi>j</mml:mi></mml:mrow></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>β</mml:mi><mml:mrow><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:mstyle></mml:mtd><mml:mtd></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:msub><mml:mi>α</mml:mi><mml:mrow><mml:mi>j</mml:mi></mml:mrow></mml:msub></mml:mstyle></mml:mtd><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mo>∼</mml:mo><mml:mtext>Normal</mml:mtext><mml:mo stretchy="false">(</mml:mo><mml:msub><mml:mi>μ</mml:mi><mml:mrow><mml:mi>y</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>σ</mml:mi><mml:mrow><mml:mi>y</mml:mi></mml:mrow></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:mstyle></mml:mtd><mml:mtd></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:msub><mml:mi>μ</mml:mi><mml:mrow><mml:mi>y</mml:mi></mml:mrow></mml:msub></mml:mstyle></mml:mtd><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mo>∼</mml:mo><mml:mtext>Normal</mml:mtext><mml:mo stretchy="false">(</mml:mo><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mn>1</mml:mn><mml:mo stretchy="false">)</mml:mo></mml:mstyle></mml:mtd><mml:mtd></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:msub><mml:mi>σ</mml:mi><mml:mrow><mml:mi>y</mml:mi></mml:mrow></mml:msub></mml:mstyle></mml:mtd><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mo>∼</mml:mo><mml:mtext>Cauchy</mml:mtext><mml:mo stretchy="false">(</mml:mo><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mn>2.5</mml:mn><mml:mo stretchy="false">)</mml:mo></mml:mstyle></mml:mtd><mml:mtd></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:msub><mml:mi>β</mml:mi><mml:mrow><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mstyle></mml:mtd><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mo>∼</mml:mo><mml:mtext>Normal</mml:mtext><mml:mo stretchy="false">(</mml:mo><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:msub><mml:mi>σ</mml:mi><mml:mrow><mml:mi>m</mml:mi></mml:mrow></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:mstyle></mml:mtd><mml:mtd></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:msub><mml:mi>σ</mml:mi><mml:mrow><mml:mi>m</mml:mi></mml:mrow></mml:msub></mml:mstyle></mml:mtd><mml:mtd><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mo>∼</mml:mo><mml:mtext>Cauchy</mml:mtext><mml:mo stretchy="false">(</mml:mo><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mn>2.5</mml:mn><mml:mo stretchy="false">)</mml:mo><mml:mo>,</mml:mo></mml:mstyle></mml:mtd><mml:mtd></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:mstyle></mml:math></disp-formula>where <inline-formula><mml:math id="inf76"><mml:msub><mml:mi>α</mml:mi><mml:mi>j</mml:mi></mml:msub></mml:math></inline-formula> represents the contribution of year to expected introduction count and <inline-formula><mml:math id="inf77"><mml:msub><mml:mi>β</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:math></inline-formula> represents the contribution of month to expected introduction count. Here, <inline-formula><mml:math id="inf78"><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mrow><mml:mrow><mml:mi mathvariant="normal">i</mml:mi><mml:mi mathvariant="normal">n</mml:mi><mml:mi mathvariant="normal">v</mml:mi><mml:mi mathvariant="normal">e</mml:mi><mml:mi mathvariant="normal">r</mml:mi><mml:mi mathvariant="normal">s</mml:mi><mml:mi mathvariant="normal">e</mml:mi><mml:mtext> </mml:mtext><mml:mi mathvariant="normal">l</mml:mi><mml:mi mathvariant="normal">o</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mi mathvariant="normal">i</mml:mi><mml:mi mathvariant="normal">t</mml:mi></mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mrow><mml:mi>j</mml:mi></mml:mrow></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>β</mml:mi><mml:mrow><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo stretchy="false">)</mml:mo><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mrow><mml:mi mathvariant="normal">e</mml:mi><mml:mi mathvariant="normal">x</mml:mi><mml:mi mathvariant="normal">p</mml:mi></mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mrow><mml:mi>j</mml:mi></mml:mrow></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>β</mml:mi><mml:mrow><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:mrow><mml:mrow><mml:mi mathvariant="normal">e</mml:mi><mml:mi mathvariant="normal">x</mml:mi><mml:mi mathvariant="normal">p</mml:mi></mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mrow><mml:mi>j</mml:mi></mml:mrow></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>β</mml:mi><mml:mrow><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo stretchy="false">)</mml:mo><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mfrac></mml:mrow></mml:mstyle></mml:math></inline-formula>. We sampled posterior values from this model via the Markov chain Monte Carlo methods implemented in Stan (<xref rid="bib17" ref-type="bibr">Carpenter et al., 2016</xref>). Odds ratios of introductions were computed for each month <inline-formula><mml:math id="inf79"><mml:mi>i</mml:mi></mml:math></inline-formula> as <inline-formula><mml:math id="inf80"><mml:mrow><mml:msub><mml:mtext>OR</mml:mtext><mml:mi>i</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mrow><mml:mi>exp</mml:mi><mml:mo></mml:mo><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:msub><mml:mi>β</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:mrow></mml:mrow></mml:math></inline-formula>.</p></sec></sec><sec id="s4-3"><title>Epidemiological analyses</title><p>Here, we employ a Monte Carlo simulation approach to identify parameters consistent with observed patterns of sequence clustering (<xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2</xref>). Our structured coalescent analyses indicate that every MERS outbreak is a contained cross-species spillover of the virus from camels into humans. The distribution of the number of these cross-species transmissions and their sizes thus contain information about the underlying transmission process. At heart, we expect fewer larger clusters if fundamental reproductive number <inline-formula><mml:math id="inf81"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> is large and more smaller clusters if <inline-formula><mml:math id="inf82"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> is small. A similar approach was used in <xref rid="bib38" ref-type="bibr">Grubaugh et al. (2017)</xref> to estimate <inline-formula><mml:math id="inf83"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> for Zika introductions into Florida.</p><p>Branching process theory provides an analytical distribution for the number of eventual cases <inline-formula><mml:math id="inf84"><mml:mi>j</mml:mi></mml:math></inline-formula> in a transmission chain resulting from a single introduction event with <inline-formula><mml:math id="inf85"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> and dispersion parameter <inline-formula><mml:math id="inf86"><mml:mi>ω</mml:mi></mml:math></inline-formula> (<xref rid="bib12" ref-type="bibr">Blumberg and Lloyd-Smith, 2013</xref>). This distribution follows<disp-formula id="equ2"><label>(1)</label><mml:math id="m2"><mml:mrow><mml:mi>Pr</mml:mi><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mi>j</mml:mi><mml:mo stretchy="false">|</mml:mo><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:mi>ω</mml:mi><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:mo>=</mml:mo><mml:mpadded width="+2.8pt"><mml:mfrac><mml:mrow><mml:mi mathvariant="normal">Γ</mml:mi><mml:mo></mml:mo><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mrow><mml:mrow><mml:mi>ω</mml:mi><mml:mo></mml:mo><mml:mi>j</mml:mi></mml:mrow><mml:mo>+</mml:mo><mml:mi>j</mml:mi></mml:mrow><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mi mathvariant="normal">Γ</mml:mi><mml:mo></mml:mo><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mi>ω</mml:mi><mml:mo></mml:mo><mml:mi>j</mml:mi></mml:mrow><mml:mo rspace="4.2pt" stretchy="false">)</mml:mo></mml:mrow><mml:mo></mml:mo><mml:mi mathvariant="normal">Γ</mml:mi><mml:mo></mml:mo><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mi>j</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:mrow></mml:mfrac></mml:mpadded><mml:mfrac><mml:msup><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mfrac><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub><mml:mi>ω</mml:mi></mml:mfrac><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:mrow><mml:mi>j</mml:mi><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup><mml:msup><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:mfrac><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub><mml:mi>ω</mml:mi></mml:mfrac></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:mrow><mml:mrow><mml:mrow><mml:mi>ω</mml:mi><mml:mo></mml:mo><mml:mi>j</mml:mi></mml:mrow><mml:mo>+</mml:mo><mml:mi>j</mml:mi></mml:mrow><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:mfrac><mml:mo>.</mml:mo></mml:mrow></mml:math></disp-formula></p><p>Here, <inline-formula><mml:math id="inf87"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> represents the expected number of secondary cases following a single infection and <inline-formula><mml:math id="inf88"><mml:mi>ω</mml:mi></mml:math></inline-formula> represents the dispersion parameter assuming secondary cases follow a negative binomial distribution (<xref rid="bib62" ref-type="bibr">Lloyd-Smith et al., 2005</xref>), so that smaller values represent larger degrees of heterogeneity in the transmission process.</p><p>As of 10 May 2017, the World Health Organization has been notified of 1952 cases of MERS-CoV (<xref rid="bib96" ref-type="bibr">World Health Organization, 2017</xref>). We thus simulated final transmission chain sizes using <xref ref-type="disp-formula" rid="equ2">Equation 1</xref> until we reached an epidemic comprised of <inline-formula><mml:math id="inf89"><mml:mrow><mml:mi>N</mml:mi><mml:mo>=</mml:mo><mml:mn>2000</mml:mn></mml:mrow></mml:math></inline-formula> cases. 10,000 simulations were run for 121 uniformly spaced values of <inline-formula><mml:math id="inf90"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> across the range [0.5–1.1] with dispersion parameter <inline-formula><mml:math id="inf91"><mml:mi>ω</mml:mi></mml:math></inline-formula> fixed to 0.1 following expectations from previous studies of coronavirus behavior (<xref rid="bib62" ref-type="bibr">Lloyd-Smith et al., 2005</xref>). Each simulation results in a vector of outbreak sizes <inline-formula><mml:math id="inf92"><mml:mi mathvariant="bold">𝐜</mml:mi></mml:math></inline-formula>, where <inline-formula><mml:math id="inf93"><mml:msub><mml:mi>c</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:math></inline-formula> is the size of the <italic>i</italic>th transmission cluster and <inline-formula><mml:math id="inf94"><mml:mrow><mml:mrow><mml:msubsup><mml:mo largeop="true" symmetric="true">∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>K</mml:mi></mml:msubsup><mml:msub><mml:mi>c</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow><mml:mo>=</mml:mo><mml:mn>2000</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="inf95"><mml:mi>K</mml:mi></mml:math></inline-formula> is the number of clusters generated.</p><p>Following the underlying transmission process generating case clusters <inline-formula><mml:math id="inf96"><mml:mi mathvariant="bold">𝐜</mml:mi></mml:math></inline-formula>, we simulate a secondary process of sampling some fraction of cases and sequencing them to generate data analogous to what we empirically observe. We sample from the case cluster size vector <inline-formula><mml:math id="inf97"><mml:mi mathvariant="bold">𝐜</mml:mi></mml:math></inline-formula> without replacement according to a multivariate hypergeometric distribution (see Algorithm 1: Multivariate hypergeometric sampling scheme). The resulting sequence cluster size vector <inline-formula><mml:math id="inf98"><mml:mi mathvariant="bold">𝐬</mml:mi></mml:math></inline-formula> contains <inline-formula><mml:math id="inf99"><mml:mi>K</mml:mi></mml:math></inline-formula> entries, some of which are zero (i.e. case clusters not sequenced), but <inline-formula><mml:math id="inf100"><mml:mrow><mml:mrow><mml:msubsup><mml:mo largeop="true" symmetric="true">∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>K</mml:mi></mml:msubsup><mml:msub><mml:mi>s</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow><mml:mo>=</mml:mo><mml:mn>174</mml:mn></mml:mrow></mml:math></inline-formula> which reflects the number of human MERS-CoV sequences used in this study. Note that this ‘sequencing capacity’ parameter does not vary over time, even though MERS-CoV sequencing efforts have varied in intensity, starting out slow due to lack of awareness, methods and materials and increasing in response to hospital outbreaks later. As the default sampling scheme operates under equiprobable sequencing, we also simulated biased sequencing by using concentrated hypergeometric distributions where the probability mass function is squared (bias = 2) or cubed (bias = 3) and then normalized. Here, bias enriches the hypergeometric distribution so that sequences are sampled with weights proportional to <inline-formula><mml:math id="inf101"><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:msubsup><mml:mi>c</mml:mi><mml:mn>1</mml:mn><mml:mi>bias</mml:mi></mml:msubsup><mml:mo>,</mml:mo><mml:msubsup><mml:mi>c</mml:mi><mml:mn>2</mml:mn><mml:mi>bias</mml:mi></mml:msubsup><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:msubsup><mml:mi>c</mml:mi><mml:mi>k</mml:mi><mml:mi>bias</mml:mi></mml:msubsup><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:math></inline-formula>. Thus, bias makes larger clusters more likely to be ‘sequenced’.</p><p>After simulations were completed, we identified simulations in which the recovered distribution of sequence cluster sizes <inline-formula><mml:math id="inf102"><mml:mi mathvariant="bold">𝐬</mml:mi></mml:math></inline-formula> fell within the 95% highest posterior density intervals for four summary statistics of empirical MERS-CoV sequence cluster sizes recovered via structured coalescent analysis: number of sequence clusters, mean, standard deviation and skewness (third central moment). These values were 48–61 for number of sequence clusters, 2.87–3.65 for mean sequence cluster size, 4.84–6.02 for standard deviation of sequence cluster sizes, and 415.40–621.06 for skewness of sequence cluster sizes.</p><p>We performed a smaller set of simulations with 2500 replicates and twice the number of cases, that is,<inline-formula><mml:math id="inf103"><mml:mrow><mml:mrow><mml:msubsup><mml:mo largeop="true" symmetric="true">∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>K</mml:mi></mml:msubsup><mml:msub><mml:mi>C</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow><mml:mo>=</mml:mo><mml:mn>4000</mml:mn></mml:mrow></mml:math></inline-formula>, to explore a dramatically underreported epidemic. Additionally, we performed additional smaller set of simulations on a rougher grid of <inline-formula><mml:math id="inf104"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></inline-formula> values (23 values, 0.50–1.05), with 5 values of dispersion parameter <inline-formula><mml:math id="inf105"><mml:mi>ω</mml:mi></mml:math></inline-formula> (0.002, 0.04, 0.1, 0.5, 1.0) and 3 levels of bias (1,2,3) to justify our choice of dispersion parameter <inline-formula><mml:math id="inf106"><mml:mi>ω</mml:mi></mml:math></inline-formula> that was fixed to 0.1 in the main analyses (<xref ref-type="fig" rid="fig3s6">Figure 3—figure supplement 6</xref>).</p></sec><sec id="s4-4"><title>Algorithm 1: Multivariate hypergeometric sampling scheme</title><p>Pseudocode describes the multivariate hypergeometric sampling scheme that simulates sequencing. Probability of sequencing a given number of cases from a case cluster depends on cluster size and sequences left (i.e. ‘sequencing capacity’). The bias parameter determines how probability mass function of the hypergeometric distribution is concentrated.</p><p><bold>Data:</bold> Array of case cluster sizes in outbreak <inline-formula><mml:math id="inf107"><mml:mrow><mml:mi mathvariant="bold">𝐜</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:msub><mml:mi>c</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>c</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:msub><mml:mi>c</mml:mi><mml:mi>K</mml:mi></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:mrow></mml:math></inline-formula>, sequences available <inline-formula><mml:math id="inf108"><mml:mi>M</mml:mi></mml:math></inline-formula>, total outbreak size <inline-formula><mml:math id="inf109"><mml:mi>N</mml:mi></mml:math></inline-formula>, where <inline-formula><mml:math id="inf110"><mml:mrow><mml:mi>N</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:msubsup><mml:mo largeop="true" symmetric="true">∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>K</mml:mi></mml:msubsup><mml:msub><mml:mi>c</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:mrow></mml:math></inline-formula>.</p><p><bold>Result:</bold> Array of sequence cluster sizes sampled: <inline-formula><mml:math id="inf111"><mml:mrow><mml:mi mathvariant="bold">𝐬</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:msub><mml:mi>s</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>s</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:msub><mml:mi>s</mml:mi><mml:mi>K</mml:mi></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:mrow></mml:math></inline-formula>.</p><p>Draw <inline-formula><mml:math id="inf112"><mml:msub><mml:mi>s</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:math></inline-formula> from a hypergeometric distribution with <inline-formula><mml:math id="inf113"><mml:msub><mml:mi>c</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:math></inline-formula> successes, <inline-formula><mml:math id="inf114"><mml:mrow><mml:mi>N</mml:mi><mml:mo>-</mml:mo><mml:msub><mml:mi>c</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> failures after <inline-formula><mml:math id="inf115"><mml:mi>M</mml:mi></mml:math></inline-formula> trials;</p><p><bold>while</bold><inline-formula><mml:math id="inf116"><mml:mrow><mml:mi>i</mml:mi><mml:mo><</mml:mo><mml:mi>K</mml:mi></mml:mrow><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mrow></mml:math></inline-formula> <bold>do</bold></p><p><inline-formula><mml:math id="inf117"><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mi>i</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mstyle></mml:math></inline-formula>;</p><p><inline-formula><mml:math id="inf118"><mml:mrow><mml:mi>M</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mi>M</mml:mi><mml:mo>-</mml:mo><mml:msub><mml:mi>s</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:mrow></mml:math></inline-formula>;</p><p> Compute the probability mass function (pmf) for all possible values of <inline-formula><mml:math id="inf119"><mml:msub><mml:mi>s</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:math></inline-formula>,</p><p><inline-formula><mml:math id="inf120"><mml:mrow><mml:mi mathvariant="bold">𝐩</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mi>p</mml:mi><mml:mo></mml:mo><mml:msup><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:mi>bias</mml:mi></mml:msup></mml:mrow><mml:mo>,</mml:mo><mml:mrow><mml:mi>p</mml:mi><mml:mo></mml:mo><mml:msup><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mn>1</mml:mn><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:mi>bias</mml:mi></mml:msup></mml:mrow><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:mrow><mml:mi>p</mml:mi><mml:mo></mml:mo><mml:msup><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:msub><mml:mi>c</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:mi>bias</mml:mi></mml:msup></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:mo>×</mml:mo><mml:msup><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:msub><mml:mo largeop="true" symmetric="true">∑</mml:mo><mml:mi>i</mml:mi></mml:msub><mml:msubsup><mml:mi>p</mml:mi><mml:mi>i</mml:mi><mml:mtext>bias</mml:mtext></mml:msubsup></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:mrow><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:mrow></mml:math></inline-formula>, where <inline-formula><mml:math id="inf121"><mml:mrow><mml:mi>p</mml:mi><mml:mo></mml:mo><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mo>⋅</mml:mo><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:mrow></mml:math></inline-formula> is the pmf for a hypergeometric distribution with <inline-formula><mml:math id="inf122"><mml:msub><mml:mi>c</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:math></inline-formula> successes, <inline-formula><mml:math id="inf123"><mml:mrow><mml:mi>N</mml:mi><mml:mo>-</mml:mo><mml:msub><mml:mi>c</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> failures after <inline-formula><mml:math id="inf124"><mml:mi>M</mml:mi></mml:math></inline-formula> trials;</p><p>Draw a sequence cluster size <inline-formula><mml:math id="inf125"><mml:msub><mml:mi>s</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:math></inline-formula> from array of potential sequence cluster sizes <inline-formula><mml:math id="inf126"><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mn>1</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:msub><mml:mi>c</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:math></inline-formula> according to <inline-formula><mml:math id="inf127"><mml:mi mathvariant="bold-italic">𝒑</mml:mi></mml:math></inline-formula>;</p><p><bold>end</bold></p><p>Add remaining sequences to last sequence cluster <inline-formula><mml:math id="inf128"><mml:mrow><mml:msub><mml:mi>c</mml:mi><mml:mi>K</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mrow><mml:mi>M</mml:mi><mml:mo>-</mml:mo><mml:msub><mml:mi>s</mml:mi><mml:mrow><mml:mi>K</mml:mi><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:mrow></mml:math></inline-formula>; </p></sec><sec id="s4-5"><title>Demographic inference of MERS-CoV in the reservoir</title><p>In order to infer the demographic history of MERS-CoV in camels we used the results of structured coalescent analyses to identify introductions of the virus into humans. The oldest sequence from each cluster introduced into humans was kept for further analysis. This procedure removes lineages coalescing rapidly in humans, which would otherwise introduce a strong signal of low effective population size. These subsampled MERS-CoV sequences from humans were combined with existing sequence data from camels to give us a dataset with minimal demographic signal coming from epidemiological processes in humans. Sequences belonging to the outgroup clade where most of MERS-CoV sequences from Egypt fall were removed out of concern that MERS epidemics in Saudi Arabia and Egypt are distinct epidemics with relatively poor sampling in the latter. Were more sequences of MERS-CoV available from other parts of Africa we speculate they would fall outside of the diversity that has been sampled in Saudi Arabia and cluster with early MERS-CoV sequences from Jordan and sequences from Egyptian camels. However, currently there are no indications of what MERS-CoV diversity looks like in camels east of Saudi Arabia. A flexible skygrid tree prior (<xref rid="bib36" ref-type="bibr">Gill et al., 2013</xref>) was used to recover estimates of scaled effective population size (<inline-formula><mml:math id="inf129"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo></mml:mo><mml:mi>τ</mml:mi></mml:mrow></mml:math></inline-formula>) at 50 evenly spaced grid points across six years, ending at the most recent tip in the tree (2015 August) in BEAST v1.8.4 (<xref rid="bib28" ref-type="bibr">Drummond et al., 2012</xref>), under a relaxed molecular clock with rates drawn from a lognormal distribution (<xref rid="bib27" ref-type="bibr">Drummond et al., 2006</xref>) and codon position partitioned (positions <inline-formula><mml:math id="inf130"><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="inf131"><mml:mn>3</mml:mn></mml:math></inline-formula>) HKY <inline-formula><mml:math id="inf132"><mml:mrow><mml:mo>+</mml:mo><mml:msub><mml:mi mathvariant="normal">Γ</mml:mi><mml:mn>4</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> (<xref rid="bib41" ref-type="bibr">Hasegawa et al., 1985</xref>; <xref rid="bib98" ref-type="bibr">Yang, 1994</xref>) nucleotide substitution models. At time of writing advanced flexible coalescent tree priors from the skyline family, such as skygrid (<xref rid="bib36" ref-type="bibr">Gill et al., 2013</xref>) are available in BEAST v1 (<xref rid="bib28" ref-type="bibr">Drummond et al., 2012</xref>) but not in BEAST v2 (<xref rid="bib14" ref-type="bibr">Bouckaert et al., 2014</xref>). We set up five independent MCMC chains to run for 500 million states, sampling every <inline-formula><mml:math id="inf133"><mml:mn>50 000</mml:mn></mml:math></inline-formula> states. This analysis suffered from poor convergence, where two chains converged onto one stationary distribution, two to another and the last chain onto a third stationary distribution, with high effective sample sizes. Demographic trajectories recovered by the two main stationary distributions are very similar and differences between the two appear to be caused by convergence onto subtly different tree topologies. This non-convergence effect may have been masked previously by the use of all available MERS-CoV sequences from humans which may have lead MCMC towards one of the multiple stationary distributions.</p><p>To ensure that recombination was not interfering with the skygrid reconstruction, we also split our MERS-CoV alignment into ten parts 2937 nucleotides long. These were then used as separate partitions with independent trees and clock rates in BEAST v1.8.4 (<xref rid="bib28" ref-type="bibr">Drummond et al., 2012</xref>). Nucleotide substitution and relaxed clock models were set up identically to the whole genome skygrid analysis described above (<xref rid="bib27" ref-type="bibr">Drummond et al., 2006</xref>; <xref rid="bib41" ref-type="bibr">Hasegawa et al., 1985</xref>; <xref rid="bib98" ref-type="bibr">Yang, 1994</xref>). Skygrid coalescent tree prior (<xref rid="bib36" ref-type="bibr">Gill et al., 2013</xref>) was used jointly across all ten partitions for demographic inference. Five MCMC chains were set up, each running for 200 million states, sampling every 20,000 states.</p></sec><sec id="s4-6"><title>Data availability</title><p>Sequence data and all analytical code is publicly available at <ext-link ext-link-type="uri" xlink:href="https://github.com/blab/mers-structure">https://github.com/blab/mers-structure</ext-link> (<xref rid="bib32" ref-type="bibr">Dudas, 2017</xref>). A copy is archived at <ext-link ext-link-type="uri" xlink:href="https://github.com/elifesciences-publications/mers-structure">https://github.com/elifesciences-publications/mers-structure</ext-link>.</p></sec></sec></body><back><sec sec-type="funding-information"><title>Funding Information</title><p>This paper was supported by the following grants:</p><list list-type="bullet"><list-item><p><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000002</institution-id><institution>National Institutes of Health</institution></institution-wrap></funding-source><award-id>R35 GM119774-01</award-id> to Trevor Bedford.</p></list-item><list-item><p><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000875</institution-id><institution>Pew Charitable Trusts</institution></institution-wrap></funding-source><award-id>Pew Biomedical Scholar</award-id> to Trevor Bedford.</p></list-item><list-item><p><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/501100000780</institution-id><institution>European Commission</institution></institution-wrap></funding-source><award-id>278433-PREDEMICS</award-id> to Andrew Rambaut.</p></list-item><list-item><p><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100010269</institution-id><institution>Wellcome</institution></institution-wrap></funding-source><award-id>206298/Z/17/Z</award-id> to Andrew Rambaut.</p></list-item><list-item><p><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100005895</institution-id><institution>Fred Hutchinson Cancer Research Center</institution></institution-wrap></funding-source><award-id>Mahan Postdoctoral Fellowship</award-id> to Gytis Dudas.</p></list-item><list-item><p><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/501100000780</institution-id><institution>European Commission</institution></institution-wrap></funding-source><award-id>725422-RESERVOIRDOCS</award-id> to Andrew Rambaut.</p></list-item></list></sec><ack id="ack"><title>Acknowledgements</title><p>We would like to thank Allison Black for useful discussion and advice. GD is supported by the Mahan postdoctoral fellowship from the Fred Hutchinson Cancer Research Center. TB is a Pew Biomedical Scholar and is supported by NIH R35 GM119774-01. AR was supported in part by the European Union Seventh Framework Programme for research, technological development and demonstration under Grant Agreement no. 278433-PREDEMICS and no. 725422-RESERVOIRDOCS, and the Wellcome Trust through project 206298/Z/17/Z.</p><p>We gratefully acknowledge the contribution of the following scientists for sharing MERS-CoV sequence data before publication:</p><p>Ali M. Somily<sup>1</sup>, Mazin Barry<sup>1</sup>, Sarah S. Al Subaie<sup>1</sup>, Abdulaziz A. BinSaeed<sup>1</sup>, Fahad A. Alzamil<sup>1</sup>, Waleed Zaher<sup>1</sup>, Theeb Al Qahtani<sup>1</sup>, Khaldoon Al Jerian<sup>1</sup>, Scott J.N. McNabb<sup>2</sup>, Imad A. Al-Jahdali<sup>3</sup>, Ahmed M. Alotaibi<sup>4</sup>, Nahid A. Batarfi<sup>5</sup>, Matthew Cotten<sup>6</sup>, Simon J. Watson<sup>6</sup>, Spela Binter<sup>6</sup>, Paul Kellam<sup>6</sup>.</p><p><sup>1</sup>College of Medicine, King Saud University, Riyadh, Kingdom of Saudi Arabia <sup>2</sup>Rollins School of Public Health, Emory University, Atlanta, GA, USA <sup>3</sup>Deputy Minister. Ex. General Director King Fahad General Hospital, Jeddah and Occupational and environmental medicine, Um AlQura University, Kingdom of Saudi Arabia <sup>4</sup>Department of Intensive Care, Prince Mohammed bin Abdulaziz Hospital, Riyadh, Kingdom of Saudi Arabia <sup>5</sup>Epidemiology section, Command and Control Center (CCC) Ministry of Health, Jeddah <sup>6</sup>Wellcome Trust Sanger Institute, Hinxton, United Kingdom</p></ack><sec id="s5" sec-type="additional-information"><title>Additional information</title><fn-group content-type="competing-interest"><title><bold>Competing interests</bold></title><fn fn-type="COI-statement" id="conf1"><p>No competing interests declared.</p></fn></fn-group><fn-group content-type="author-contribution"><title><bold>Author contributions</bold></title><fn fn-type="con" id="con1"><p>Conceptualization, Data curation, Software, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing.</p></fn><fn fn-type="con" id="con2"><p>Software, Formal analysis, Investigation, Methodology, Writing—review and editing.</p></fn><fn fn-type="con" id="con3"><p>Conceptualization, Data curation, Supervision, Funding acquisition, Methodology, Writing—review and editing.</p></fn><fn fn-type="con" id="con4"><p>Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Project administration, Writing—review and editing.</p></fn></fn-group></sec><sec id="s6" sec-type="supplementary-material"><title>Additional files</title><supplementary-material content-type="local-data" id="sdata1"><object-id pub-id-type="doi">10.7554/eLife.31257.033</object-id><label>Source data 1.</label><caption><title>MERS-CoV sequences used in the study.</title></caption><media mime-subtype="zip" mimetype="application" xlink:href="elife-31257-data1.zip" orientation="portrait" id="d35e3737" position="anchor"></media></supplementary-material><supplementary-material content-type="local-data" id="supp1"><object-id pub-id-type="doi">10.7554/eLife.31257.034</object-id><label>Supplementary file 1.</label><caption><title>Strain names, accessions (where available), identified host and reported collection dates for MERS-CoV genomes used in this study.</title></caption><media mime-subtype="tab-separated-values" mimetype="text" xlink:href="elife-31257-supp1.tsv" orientation="portrait" id="d35e3746" position="anchor"></media></supplementary-material><supplementary-material content-type="local-data" id="transrepform"><object-id pub-id-type="doi">10.7554/eLife.31257.035</object-id><label>Transparent reporting form</label><media mime-subtype="pdf" mimetype="application" xlink:href="elife-31257-transrepform.pdf" orientation="portrait" id="d35e3752" position="anchor"></media></supplementary-material></sec><ref-list><title>References</title><ref id="bib1"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Abdallah</surname><given-names>H</given-names></name><name><surname>Faye</surname><given-names>B</given-names></name></person-group><year>2013</year><article-title>Typology of camel farming system in Saudi Arabia</article-title><source>Emirates Journal of Food and Agriculture</source><volume>25</volume><elocation-id>250</elocation-id><pub-id pub-id-type="doi">10.9755/ejfa.v25i4.15491</pub-id></element-citation></ref><ref id="bib2"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Adney</surname><given-names>DR</given-names></name><name><surname>van Doremalen</surname><given-names>N</given-names></name><name><surname>Brown</surname><given-names>VR</given-names></name><name><surname>Bushmaker</surname><given-names>T</given-names></name><name><surname>Scott</surname><given-names>D</given-names></name><name><surname>de Wit</surname><given-names>E</given-names></name><name><surname>Bowen</surname><given-names>RA</given-names></name><name><surname>Munster</surname><given-names>VJ</given-names></name></person-group><year>2014</year><article-title>Replication and shedding of MERS-CoV in upper respiratory tract of inoculated dromedary camels</article-title><source>Emerging Infectious Diseases</source><volume>20</volume><fpage>1999</fpage><lpage>2005</lpage><pub-id pub-id-type="doi">10.3201/eid2012.141280</pub-id><pub-id pub-id-type="pmid">25418529</pub-id></element-citation></ref><ref id="bib3"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Ali</surname><given-names>MA</given-names></name><name><surname>Shehata</surname><given-names>MM</given-names></name><name><surname>Gomaa</surname><given-names>MR</given-names></name><name><surname>Kandeil</surname><given-names>A</given-names></name><name><surname>El-Shesheny</surname><given-names>R</given-names></name><name><surname>Kayed</surname><given-names>AS</given-names></name><name><surname>El-Taweel</surname><given-names>AN</given-names></name><name><surname>Atea</surname><given-names>M</given-names></name><name><surname>Hassan</surname><given-names>N</given-names></name><name><surname>Bagato</surname><given-names>O</given-names></name><name><surname>Moatasim</surname><given-names>Y</given-names></name><name><surname>Mahmoud</surname><given-names>SH</given-names></name><name><surname>Kutkat</surname><given-names>O</given-names></name><name><surname>Maatouq</surname><given-names>AM</given-names></name><name><surname>Osman</surname><given-names>A</given-names></name><name><surname>McKenzie</surname><given-names>PP</given-names></name><name><surname>Webby</surname><given-names>RJ</given-names></name><name><surname>Kayali</surname><given-names>G</given-names></name><name><surname>Systematic</surname><given-names>KG</given-names></name></person-group><year>2017</year><article-title>Systematic, active surveillance for Middle East respiratory syndrome coronavirus in camels in Egypt</article-title><source>Emerging Microbes & Infections</source><volume>6</volume><elocation-id>e1</elocation-id><pub-id pub-id-type="doi">10.1038/emi.2016.130</pub-id><pub-id pub-id-type="pmid">28050021</pub-id></element-citation></ref><ref id="bib4"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Almutairi</surname><given-names>SE</given-names></name><name><surname>Boujenane</surname><given-names>I</given-names></name><name><surname>Musaad</surname><given-names>A</given-names></name><name><surname>Awad-Acharari</surname><given-names>F</given-names></name></person-group><year>2010</year><article-title>Non-genetic factors influencing reproductive traits and calving weight in Saudi camels</article-title><source>Tropical Animal Health and Production</source><volume>42</volume><fpage>1087</fpage><lpage>1092</lpage><pub-id pub-id-type="doi">10.1007/s11250-010-9529-y</pub-id><pub-id pub-id-type="pmid">20195755</pub-id></element-citation></ref><ref id="bib5"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Antia</surname><given-names>R</given-names></name><name><surname>Regoes</surname><given-names>RR</given-names></name><name><surname>Koella</surname><given-names>JC</given-names></name><name><surname>Bergstrom</surname><given-names>CT</given-names></name></person-group><year>2003</year><article-title>The role of evolution in the emergence of infectious diseases</article-title><source>Nature</source><volume>426</volume><fpage>658</fpage><lpage>661</lpage><pub-id pub-id-type="doi">10.1038/nature02104</pub-id><pub-id pub-id-type="pmid">14668863</pub-id></element-citation></ref><ref id="bib6"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Assiri</surname><given-names>A</given-names></name><name><surname>Al-Tawfiq</surname><given-names>JA</given-names></name><name><surname>Al-Rabeeah</surname><given-names>AA</given-names></name><name><surname>Al-Rabiah</surname><given-names>FA</given-names></name><name><surname>Al-Hajjar</surname><given-names>S</given-names></name><name><surname>Al-Barrak</surname><given-names>A</given-names></name><name><surname>Flemban</surname><given-names>H</given-names></name><name><surname>Al-Nassir</surname><given-names>WN</given-names></name><name><surname>Balkhy</surname><given-names>HH</given-names></name><name><surname>Al-Hakeem</surname><given-names>RF</given-names></name><name><surname>Makhdoom</surname><given-names>HQ</given-names></name><name><surname>Zumla</surname><given-names>AI</given-names></name><name><surname>Memish</surname><given-names>ZA</given-names></name><name><surname>Epidemiological</surname><given-names>MZA</given-names></name></person-group><year>2013a</year><article-title>Epidemiological, demographic, and clinical characteristics of 47 cases of Middle East respiratory syndrome coronavirus disease from Saudi Arabia: a descriptive study</article-title><source>The Lancet Infectious Diseases</source><volume>13</volume><fpage>752</fpage><lpage>761</lpage><pub-id pub-id-type="doi">10.1016/S1473-3099(13)70204-4</pub-id><pub-id pub-id-type="pmid">23891402</pub-id></element-citation></ref><ref id="bib7"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Assiri</surname><given-names>A</given-names></name><name><surname>McGeer</surname><given-names>A</given-names></name><name><surname>Perl</surname><given-names>TM</given-names></name><name><surname>Price</surname><given-names>CS</given-names></name><name><surname>Al Rabeeah</surname><given-names>AA</given-names></name><name><surname>Cummings</surname><given-names>DA</given-names></name><name><surname>Alabdullatif</surname><given-names>ZN</given-names></name><name><surname>Assad</surname><given-names>M</given-names></name><name><surname>Almulhim</surname><given-names>A</given-names></name><name><surname>Makhdoom</surname><given-names>H</given-names></name><name><surname>Madani</surname><given-names>H</given-names></name><name><surname>Alhakeem</surname><given-names>R</given-names></name><name><surname>Al-Tawfiq</surname><given-names>JA</given-names></name><name><surname>Cotten</surname><given-names>M</given-names></name><name><surname>Watson</surname><given-names>SJ</given-names></name><name><surname>Kellam</surname><given-names>P</given-names></name><name><surname>Zumla</surname><given-names>AI</given-names></name><name><surname>Memish</surname><given-names>ZA</given-names></name><collab>KSA MERS-CoV Investigation Team</collab></person-group><year>2013b</year><article-title>Hospital outbreak of Middle East respiratory syndrome coronavirus</article-title><source>New England Journal of Medicine</source><volume>369</volume><fpage>407</fpage><lpage>416</lpage><pub-id pub-id-type="doi">10.1056/NEJMoa1306742</pub-id><pub-id pub-id-type="pmid">23782161</pub-id></element-citation></ref><ref id="bib8"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Assiri</surname><given-names>AM</given-names></name><name><surname>Biggs</surname><given-names>HM</given-names></name><name><surname>Abedi</surname><given-names>GR</given-names></name><name><surname>Lu</surname><given-names>X</given-names></name><name><surname>Bin Saeed</surname><given-names>A</given-names></name><name><surname>Abdalla</surname><given-names>O</given-names></name><name><surname>Mohammed</surname><given-names>M</given-names></name><name><surname>Al-Abdely</surname><given-names>HM</given-names></name><name><surname>Algarni</surname><given-names>HS</given-names></name><name><surname>Alhakeem</surname><given-names>RF</given-names></name><name><surname>Almasri</surname><given-names>MM</given-names></name><name><surname>Alsharef</surname><given-names>AA</given-names></name><name><surname>Nooh</surname><given-names>R</given-names></name><name><surname>Erdman</surname><given-names>DD</given-names></name><name><surname>Gerber</surname><given-names>SI</given-names></name><name><surname>Watson</surname><given-names>JT</given-names></name></person-group><year>2016a</year><article-title>Increase in Middle East Respiratory Syndrome-Coronavirus Cases in Saudi Arabia Linked to Hospital Outbreak With Continued Circulation of Recombinant Virus, July 1-August 31, 2015</article-title><source>Open Forum Infectious Diseases</source><volume>3</volume><fpage>ofw165</fpage><pub-id pub-id-type="doi">10.1093/ofid/ofw165</pub-id><pub-id pub-id-type="pmid">27704019</pub-id></element-citation></ref><ref id="bib9"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Assiri</surname><given-names>AM</given-names></name><name><surname>Midgley</surname><given-names>CM</given-names></name><name><surname>Abedi</surname><given-names>GR</given-names></name><name><surname>Bin Saeed</surname><given-names>A</given-names></name><name><surname>Almasri</surname><given-names>MM</given-names></name><name><surname>Lu</surname><given-names>X</given-names></name><name><surname>Al-Abdely</surname><given-names>HM</given-names></name><name><surname>Abdalla</surname><given-names>O</given-names></name><name><surname>Mohammed</surname><given-names>M</given-names></name><name><surname>Algarni</surname><given-names>HS</given-names></name><name><surname>Alhakeem</surname><given-names>RF</given-names></name><name><surname>Sakthivel</surname><given-names>SK</given-names></name><name><surname>Nooh</surname><given-names>R</given-names></name><name><surname>Alshayab</surname><given-names>Z</given-names></name><name><surname>Alessa</surname><given-names>M</given-names></name><name><surname>Srinivasamoorthy</surname><given-names>G</given-names></name><name><surname>AlQahtani</surname><given-names>SY</given-names></name><name><surname>Kheyami</surname><given-names>A</given-names></name><name><surname>HajOmar</surname><given-names>WH</given-names></name><name><surname>Banaser</surname><given-names>TM</given-names></name><name><surname>Esmaeel</surname><given-names>A</given-names></name><name><surname>Hall</surname><given-names>AJ</given-names></name><name><surname>Curns</surname><given-names>AT</given-names></name><name><surname>Tamin</surname><given-names>A</given-names></name><name><surname>Alsharef</surname><given-names>AA</given-names></name><name><surname>Erdman</surname><given-names>D</given-names></name><name><surname>Watson</surname><given-names>JT</given-names></name><name><surname>Gerber</surname><given-names>SI</given-names></name></person-group><year>2016b</year><article-title>Epidemiology of a Novel Recombinant Middle East Respiratory Syndrome Coronavirus in Humans in Saudi Arabia</article-title><source>Journal of Infectious Diseases</source><volume>214</volume><fpage>712</fpage><lpage>721</lpage><pub-id pub-id-type="doi">10.1093/infdis/jiw236</pub-id><pub-id pub-id-type="pmid">27302191</pub-id></element-citation></ref><ref id="bib10"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Azhar</surname><given-names>EI</given-names></name><name><surname>El-Kafrawy</surname><given-names>SA</given-names></name><name><surname>Farraj</surname><given-names>SA</given-names></name><name><surname>Hassan</surname><given-names>AM</given-names></name><name><surname>Al-Saeed</surname><given-names>MS</given-names></name><name><surname>Hashem</surname><given-names>AM</given-names></name><name><surname>Madani</surname><given-names>TA</given-names></name></person-group><year>2014</year><article-title>Evidence for camel-to-human transmission of MERS coronavirus</article-title><source>New England Journal of Medicine</source><volume>370</volume><fpage>2499</fpage><lpage>2505</lpage><pub-id pub-id-type="doi">10.1056/NEJMoa1401505</pub-id><pub-id pub-id-type="pmid">24896817</pub-id></element-citation></ref><ref id="bib11"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Bedford</surname><given-names>T</given-names></name><name><surname>Cobey</surname><given-names>S</given-names></name><name><surname>Pascual</surname><given-names>M</given-names></name></person-group><year>2011</year><article-title>Strength and tempo of selection revealed in viral gene genealogies</article-title><source>BMC Evolutionary Biology</source><volume>11</volume><elocation-id>220</elocation-id><pub-id pub-id-type="doi">10.1186/1471-2148-11-220</pub-id><pub-id pub-id-type="pmid">21787390</pub-id></element-citation></ref><ref id="bib12"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Blumberg</surname><given-names>S</given-names></name><name><surname>Lloyd-Smith</surname><given-names>JO</given-names></name></person-group><year>2013</year><article-title>Inference of R(0) and transmission heterogeneity from the size distribution of stuttering chains</article-title><source>PLoS Computational Biology</source><volume>9</volume><elocation-id>e1002993</elocation-id><pub-id pub-id-type="doi">10.1371/journal.pcbi.1002993</pub-id><pub-id pub-id-type="pmid">23658504</pub-id></element-citation></ref><ref id="bib13"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Boni</surname><given-names>MF</given-names></name><name><surname>Posada</surname><given-names>D</given-names></name><name><surname>Feldman</surname><given-names>MW</given-names></name></person-group><year>2007</year><article-title>An exact nonparametric method for inferring mosaic structure in sequence triplets</article-title><source>Genetics</source><volume>176</volume><fpage>1035</fpage><lpage>1047</lpage><pub-id pub-id-type="doi">10.1534/genetics.106.068874</pub-id><pub-id pub-id-type="pmid">17409078</pub-id></element-citation></ref><ref id="bib14"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Bouckaert</surname><given-names>R</given-names></name><name><surname>Heled</surname><given-names>J</given-names></name><name><surname>Kühnert</surname><given-names>D</given-names></name><name><surname>Vaughan</surname><given-names>T</given-names></name><name><surname>Wu</surname><given-names>CH</given-names></name><name><surname>Xie</surname><given-names>D</given-names></name><name><surname>Suchard</surname><given-names>MA</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name><name><surname>Drummond</surname><given-names>AJ</given-names></name></person-group><year>2014</year><article-title>BEAST 2: a software platform for Bayesian evolutionary analysis</article-title><source>PLoS Computational Biology</source><volume>10</volume><elocation-id>e1003537</elocation-id><pub-id pub-id-type="doi">10.1371/journal.pcbi.1003537</pub-id><pub-id pub-id-type="pmid">24722319</pub-id></element-citation></ref><ref id="bib15"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Briese</surname><given-names>T</given-names></name><name><surname>Mishra</surname><given-names>N</given-names></name><name><surname>Jain</surname><given-names>K</given-names></name><name><surname>Zalmout</surname><given-names>IS</given-names></name><name><surname>Jabado</surname><given-names>OJ</given-names></name><name><surname>Karesh</surname><given-names>WB</given-names></name><name><surname>Daszak</surname><given-names>P</given-names></name><name><surname>Mohammed</surname><given-names>OB</given-names></name><name><surname>Alagaili</surname><given-names>AN</given-names></name><name><surname>Lipkin</surname><given-names>WI</given-names></name></person-group><year>2014</year><article-title>Middle East respiratory syndrome coronavirus quasispecies that include homologues of human isolates revealed through whole-genome analysis and virus cultured from dromedary camels in Saudi Arabia</article-title><source>mBio</source><volume>5</volume><fpage>e01146-14</fpage><lpage>14</lpage><pub-id pub-id-type="doi">10.1128/mBio.01146-14</pub-id><pub-id pub-id-type="pmid">24781747</pub-id></element-citation></ref><ref id="bib16"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Bruen</surname><given-names>TC</given-names></name><name><surname>Philippe</surname><given-names>H</given-names></name><name><surname>Bryant</surname><given-names>D</given-names></name></person-group><year>2006</year><article-title>A simple and robust statistical test for detecting the presence of recombination</article-title><source>Genetics</source><volume>172</volume><fpage>2665</fpage><lpage>2681</lpage><pub-id pub-id-type="doi">10.1534/genetics.105.048975</pub-id><pub-id pub-id-type="pmid">16489234</pub-id></element-citation></ref><ref id="bib17"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Carpenter</surname><given-names>B</given-names></name><name><surname>Gelman</surname><given-names>A</given-names></name><name><surname>Hoffman</surname><given-names>M</given-names></name><name><surname>Lee</surname><given-names>D</given-names></name><name><surname>Goodrich</surname><given-names>B</given-names></name><name><surname>Betancourt</surname><given-names>M</given-names></name><name><surname>Brubaker</surname><given-names>MA</given-names></name><name><surname>Guo</surname><given-names>J</given-names></name><name><surname>Li</surname><given-names>P</given-names></name><name><surname>Riddell</surname><given-names>A</given-names></name></person-group><year>2016</year><article-title>Stan: A probabilistic programming language</article-title><source>Journal of Statistical Software</source><volume>20</volume><fpage>1</fpage><lpage>37</lpage><pub-id pub-id-type="doi">10.18637/jss.v076.i01</pub-id></element-citation></ref><ref id="bib18"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Cauchemez</surname><given-names>S</given-names></name><name><surname>Nouvellet</surname><given-names>P</given-names></name><name><surname>Cori</surname><given-names>A</given-names></name><name><surname>Jombart</surname><given-names>T</given-names></name><name><surname>Garske</surname><given-names>T</given-names></name><name><surname>Clapham</surname><given-names>H</given-names></name><name><surname>Moore</surname><given-names>S</given-names></name><name><surname>Mills</surname><given-names>HL</given-names></name><name><surname>Salje</surname><given-names>H</given-names></name><name><surname>Collins</surname><given-names>C</given-names></name><name><surname>Rodriquez-Barraquer</surname><given-names>I</given-names></name><name><surname>Riley</surname><given-names>S</given-names></name><name><surname>Truelove</surname><given-names>S</given-names></name><name><surname>Algarni</surname><given-names>H</given-names></name><name><surname>Alhakeem</surname><given-names>R</given-names></name><name><surname>AlHarbi</surname><given-names>K</given-names></name><name><surname>Turkistani</surname><given-names>A</given-names></name><name><surname>Aguas</surname><given-names>RJ</given-names></name><name><surname>Cummings</surname><given-names>DA</given-names></name><name><surname>Van Kerkhove</surname><given-names>MD</given-names></name><name><surname>Donnelly</surname><given-names>CA</given-names></name><name><surname>Lessler</surname><given-names>J</given-names></name><name><surname>Fraser</surname><given-names>C</given-names></name><name><surname>Al-Barrak</surname><given-names>A</given-names></name><name><surname>Ferguson</surname><given-names>NM</given-names></name></person-group><year>2016</year><article-title>Unraveling the drivers of MERS-CoV transmission</article-title><source>PNAS</source><volume>113</volume><fpage>9081</fpage><lpage>9086</lpage><pub-id pub-id-type="doi">10.1073/pnas.1519235113</pub-id><pub-id pub-id-type="pmid">27457935</pub-id></element-citation></ref><ref id="bib19"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Chen</surname><given-names>X</given-names></name><name><surname>Chughtai</surname><given-names>AA</given-names></name><name><surname>Dyda</surname><given-names>A</given-names></name><name><surname>MacIntyre</surname><given-names>CR</given-names></name></person-group><year>2017</year><article-title>Comparative epidemiology of Middle East respiratory syndrome coronavirus (MERS-CoV) in Saudi Arabia and South Korea</article-title><source>Emerging Microbes & Infections</source><volume>6</volume><elocation-id>e51</elocation-id><pub-id pub-id-type="doi">10.1038/emi.2017.40</pub-id><pub-id pub-id-type="pmid">28588290</pub-id></element-citation></ref><ref id="bib20"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Chu</surname><given-names>DK</given-names></name><name><surname>Poon</surname><given-names>LL</given-names></name><name><surname>Gomaa</surname><given-names>MM</given-names></name><name><surname>Shehata</surname><given-names>MM</given-names></name><name><surname>Perera</surname><given-names>RA</given-names></name><name><surname>Abu Zeid</surname><given-names>D</given-names></name><name><surname>El Rifay</surname><given-names>AS</given-names></name><name><surname>Siu</surname><given-names>LY</given-names></name><name><surname>Guan</surname><given-names>Y</given-names></name><name><surname>Webby</surname><given-names>RJ</given-names></name><name><surname>Ali</surname><given-names>MA</given-names></name><name><surname>Peiris</surname><given-names>M</given-names></name><name><surname>Kayali</surname><given-names>G</given-names></name></person-group><year>2014</year><article-title>MERS coronaviruses in dromedary camels, Egypt</article-title><source>Emerging Infectious Diseases</source><volume>20</volume><fpage>1049</fpage><lpage>1053</lpage><pub-id pub-id-type="doi">10.3201/eid2006.140299</pub-id><pub-id pub-id-type="pmid">24856660</pub-id></element-citation></ref><ref id="bib21"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Corman</surname><given-names>VM</given-names></name><name><surname>Jores</surname><given-names>J</given-names></name><name><surname>Meyer</surname><given-names>B</given-names></name><name><surname>Younan</surname><given-names>M</given-names></name><name><surname>Liljander</surname><given-names>A</given-names></name><name><surname>Said</surname><given-names>MY</given-names></name><name><surname>Gluecks</surname><given-names>I</given-names></name><name><surname>Lattwein</surname><given-names>E</given-names></name><name><surname>Bosch</surname><given-names>BJ</given-names></name><name><surname>Drexler</surname><given-names>JF</given-names></name><name><surname>Bornstein</surname><given-names>S</given-names></name><name><surname>Drosten</surname><given-names>C</given-names></name><name><surname>Müller</surname><given-names>MA</given-names></name></person-group><year>2014</year><article-title>Antibodies against MERS coronavirus in dromedary camels, Kenya, 1992-2013</article-title><source>Emerging Infectious Diseases</source><volume>20</volume><fpage>1319</fpage><lpage>1322</lpage><pub-id pub-id-type="doi">10.3201/eid2008.140596</pub-id><pub-id pub-id-type="pmid">25075637</pub-id></element-citation></ref><ref id="bib22"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Cotten</surname><given-names>M</given-names></name><name><surname>Watson</surname><given-names>SJ</given-names></name><name><surname>Kellam</surname><given-names>P</given-names></name><name><surname>Al-Rabeeah</surname><given-names>AA</given-names></name><name><surname>Makhdoom</surname><given-names>HQ</given-names></name><name><surname>Assiri</surname><given-names>A</given-names></name><name><surname>Al-Tawfiq</surname><given-names>JA</given-names></name><name><surname>Alhakeem</surname><given-names>RF</given-names></name><name><surname>Madani</surname><given-names>H</given-names></name><name><surname>AlRabiah</surname><given-names>FA</given-names></name><name><surname>Al Hajjar</surname><given-names>S</given-names></name><name><surname>Al-nassir</surname><given-names>WN</given-names></name><name><surname>Albarrak</surname><given-names>A</given-names></name><name><surname>Flemban</surname><given-names>H</given-names></name><name><surname>Balkhy</surname><given-names>HH</given-names></name><name><surname>Alsubaie</surname><given-names>S</given-names></name><name><surname>Palser</surname><given-names>AL</given-names></name><name><surname>Gall</surname><given-names>A</given-names></name><name><surname>Bashford-Rogers</surname><given-names>R</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name><name><surname>Zumla</surname><given-names>AI</given-names></name><name><surname>Memish</surname><given-names>ZA</given-names></name></person-group><year>2013</year><article-title>Transmission and evolution of the Middle East respiratory syndrome coronavirus in Saudi Arabia: a descriptive genomic study</article-title><source>The Lancet</source><volume>382</volume><fpage>1993</fpage><lpage>2002</lpage><pub-id pub-id-type="doi">10.1016/S0140-6736(13)61887-5</pub-id><pub-id pub-id-type="pmid">24055451</pub-id></element-citation></ref><ref id="bib23"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Cotten</surname><given-names>M</given-names></name><name><surname>Watson</surname><given-names>SJ</given-names></name><name><surname>Zumla</surname><given-names>AI</given-names></name><name><surname>Makhdoom</surname><given-names>HQ</given-names></name><name><surname>Palser</surname><given-names>AL</given-names></name><name><surname>Ong</surname><given-names>SH</given-names></name><name><surname>Al Rabeeah</surname><given-names>AA</given-names></name><name><surname>Alhakeem</surname><given-names>RF</given-names></name><name><surname>Assiri</surname><given-names>A</given-names></name><name><surname>Al-Tawfiq</surname><given-names>JA</given-names></name><name><surname>Albarrak</surname><given-names>A</given-names></name><name><surname>Barry</surname><given-names>M</given-names></name><name><surname>Shibl</surname><given-names>A</given-names></name><name><surname>Alrabiah</surname><given-names>FA</given-names></name><name><surname>Hajjar</surname><given-names>S</given-names></name><name><surname>Balkhy</surname><given-names>HH</given-names></name><name><surname>Flemban</surname><given-names>H</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name><name><surname>Kellam</surname><given-names>P</given-names></name><name><surname>Memish</surname><given-names>ZA</given-names></name></person-group><year>2014</year><article-title>Spread, circulation, and evolution of the Middle East respiratory syndrome coronavirus</article-title><source>mBio</source><volume>5</volume><fpage>e01062-13</fpage><pub-id pub-id-type="doi">10.1128/mBio.01062-13</pub-id><pub-id pub-id-type="pmid">24549846</pub-id></element-citation></ref><ref id="bib24"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>De Maio</surname><given-names>N</given-names></name><name><surname>Wu</surname><given-names>CH</given-names></name><name><surname>O'Reilly</surname><given-names>KM</given-names></name><name><surname>Wilson</surname><given-names>D</given-names></name></person-group><year>2015</year><article-title>New routes to phylogeography: A Bayesian structured coalescent approximation</article-title><source>PLOS Genetics</source><volume>11</volume><elocation-id>e1005421</elocation-id><pub-id pub-id-type="doi">10.1371/journal.pgen.1005421</pub-id><pub-id pub-id-type="pmid">26267488</pub-id></element-citation></ref><ref id="bib25"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Drosten</surname><given-names>C</given-names></name><name><surname>Muth</surname><given-names>D</given-names></name><name><surname>Corman</surname><given-names>VM</given-names></name><name><surname>Hussain</surname><given-names>R</given-names></name><name><surname>Al Masri</surname><given-names>M</given-names></name><name><surname>HajOmar</surname><given-names>W</given-names></name><name><surname>Landt</surname><given-names>O</given-names></name><name><surname>Assiri</surname><given-names>A</given-names></name><name><surname>Eckerle</surname><given-names>I</given-names></name><name><surname>Al Shangiti</surname><given-names>A</given-names></name><name><surname>Al-Tawfiq</surname><given-names>JA</given-names></name><name><surname>Albarrak</surname><given-names>A</given-names></name><name><surname>Zumla</surname><given-names>A</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name><name><surname>Memish</surname><given-names>ZA</given-names></name></person-group><year>2015</year><article-title>An observational, laboratory-based study of outbreaks of Middle East respiratory syndrome coronavirus in Jeddah and Riyadh, Kingdom of Saudi Arabia, 2014</article-title><source>Clinical Infectious Diseases</source><volume>60</volume><fpage>369</fpage><lpage>377</lpage><pub-id pub-id-type="doi">10.1093/cid/ciu812</pub-id><pub-id pub-id-type="pmid">25323704</pub-id></element-citation></ref><ref id="bib26"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Drosten</surname><given-names>C</given-names></name><name><surname>Seilmaier</surname><given-names>M</given-names></name><name><surname>Corman</surname><given-names>VM</given-names></name><name><surname>Hartmann</surname><given-names>W</given-names></name><name><surname>Scheible</surname><given-names>G</given-names></name><name><surname>Sack</surname><given-names>S</given-names></name><name><surname>Guggemos</surname><given-names>W</given-names></name><name><surname>Kallies</surname><given-names>R</given-names></name><name><surname>Muth</surname><given-names>D</given-names></name><name><surname>Junglen</surname><given-names>S</given-names></name><name><surname>Müller</surname><given-names>MA</given-names></name><name><surname>Haas</surname><given-names>W</given-names></name><name><surname>Guberina</surname><given-names>H</given-names></name><name><surname>Röhnisch</surname><given-names>T</given-names></name><name><surname>Schmid-Wendtner</surname><given-names>M</given-names></name><name><surname>Aldabbagh</surname><given-names>S</given-names></name><name><surname>Dittmer</surname><given-names>U</given-names></name><name><surname>Gold</surname><given-names>H</given-names></name><name><surname>Graf</surname><given-names>P</given-names></name><name><surname>Bonin</surname><given-names>F</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name><name><surname>Wendtner</surname><given-names>CM</given-names></name></person-group><year>2013</year><article-title>Clinical features and virological analysis of a case of Middle East respiratory syndrome coronavirus infection</article-title><source>The Lancet Infectious Diseases</source><volume>13</volume><fpage>745</fpage><lpage>751</lpage><pub-id pub-id-type="doi">10.1016/S1473-3099(13)70154-3</pub-id><pub-id pub-id-type="pmid">23782859</pub-id></element-citation></ref><ref id="bib27"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Drummond</surname><given-names>AJ</given-names></name><name><surname>Ho</surname><given-names>SY</given-names></name><name><surname>Phillips</surname><given-names>MJ</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name></person-group><year>2006</year><article-title>Relaxed phylogenetics and dating with confidence</article-title><source>PLoS Biology</source><volume>4</volume><elocation-id>e88</elocation-id><pub-id pub-id-type="doi">10.1371/journal.pbio.0040088</pub-id><pub-id pub-id-type="pmid">16683862</pub-id></element-citation></ref><ref id="bib28"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Drummond</surname><given-names>AJ</given-names></name><name><surname>Suchard</surname><given-names>MA</given-names></name><name><surname>Xie</surname><given-names>D</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name></person-group><year>2012</year><article-title>Bayesian phylogenetics with BEAUti and the BEAST 1.7</article-title><source>Molecular Biology and Evolution</source><volume>29</volume><fpage>1969</fpage><lpage>1973</lpage><pub-id pub-id-type="doi">10.1093/molbev/mss075</pub-id><pub-id pub-id-type="pmid">22367748</pub-id></element-citation></ref><ref id="bib29"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Dudas</surname><given-names>G</given-names></name><name><surname>Bedford</surname><given-names>T</given-names></name><name><surname>Lycett</surname><given-names>S</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name></person-group><year>2015</year><article-title>Reassortment between influenza B lineages and the emergence of a coadapted PB1-PB2-HA gene complex</article-title><source>Molecular Biology and Evolution</source><volume>32</volume><fpage>162</fpage><lpage>172</lpage><pub-id pub-id-type="doi">10.1093/molbev/msu287</pub-id><pub-id pub-id-type="pmid">25323575</pub-id></element-citation></ref><ref id="bib30"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Dudas</surname><given-names>G</given-names></name><name><surname>Carvalho</surname><given-names>LM</given-names></name><name><surname>Bedford</surname><given-names>T</given-names></name><name><surname>Tatem</surname><given-names>AJ</given-names></name><name><surname>Baele</surname><given-names>G</given-names></name><name><surname>Faria</surname><given-names>NR</given-names></name><name><surname>Park</surname><given-names>DJ</given-names></name><name><surname>Ladner</surname><given-names>JT</given-names></name><name><surname>Arias</surname><given-names>A</given-names></name><name><surname>Asogun</surname><given-names>D</given-names></name><name><surname>Bielejec</surname><given-names>F</given-names></name><name><surname>Caddy</surname><given-names>SL</given-names></name><name><surname>Cotten</surname><given-names>M</given-names></name><name><surname>D'Ambrozio</surname><given-names>J</given-names></name><name><surname>Dellicour</surname><given-names>S</given-names></name><name><surname>Di Caro</surname><given-names>A</given-names></name><name><surname>Diclaro</surname><given-names>JW</given-names></name><name><surname>Duraffour</surname><given-names>S</given-names></name><name><surname>Elmore</surname><given-names>MJ</given-names></name><name><surname>Fakoli</surname><given-names>LS</given-names></name><name><surname>Faye</surname><given-names>O</given-names></name><name><surname>Gilbert</surname><given-names>ML</given-names></name><name><surname>Gevao</surname><given-names>SM</given-names></name><name><surname>Gire</surname><given-names>S</given-names></name><name><surname>Gladden-Young</surname><given-names>A</given-names></name><name><surname>Gnirke</surname><given-names>A</given-names></name><name><surname>Goba</surname><given-names>A</given-names></name><name><surname>Grant</surname><given-names>DS</given-names></name><name><surname>Haagmans</surname><given-names>BL</given-names></name><name><surname>Hiscox</surname><given-names>JA</given-names></name><name><surname>Jah</surname><given-names>U</given-names></name><name><surname>Kugelman</surname><given-names>JR</given-names></name><name><surname>Liu</surname><given-names>D</given-names></name><name><surname>Lu</surname><given-names>J</given-names></name><name><surname>Malboeuf</surname><given-names>CM</given-names></name><name><surname>Mate</surname><given-names>S</given-names></name><name><surname>Matthews</surname><given-names>DA</given-names></name><name><surname>Matranga</surname><given-names>CB</given-names></name><name><surname>Meredith</surname><given-names>LW</given-names></name><name><surname>Qu</surname><given-names>J</given-names></name><name><surname>Quick</surname><given-names>J</given-names></name><name><surname>Pas</surname><given-names>SD</given-names></name><name><surname>Phan</surname><given-names>MVT</given-names></name><name><surname>Pollakis</surname><given-names>G</given-names></name><name><surname>Reusken</surname><given-names>CB</given-names></name><name><surname>Sanchez-Lockhart</surname><given-names>M</given-names></name><name><surname>Schaffner</surname><given-names>SF</given-names></name><name><surname>Schieffelin</surname><given-names>JS</given-names></name><name><surname>Sealfon</surname><given-names>RS</given-names></name><name><surname>Simon-Loriere</surname><given-names>E</given-names></name><name><surname>Smits</surname><given-names>SL</given-names></name><name><surname>Stoecker</surname><given-names>K</given-names></name><name><surname>Thorne</surname><given-names>L</given-names></name><name><surname>Tobin</surname><given-names>EA</given-names></name><name><surname>Vandi</surname><given-names>MA</given-names></name><name><surname>Watson</surname><given-names>SJ</given-names></name><name><surname>West</surname><given-names>K</given-names></name><name><surname>Whitmer</surname><given-names>S</given-names></name><name><surname>Wiley</surname><given-names>MR</given-names></name><name><surname>Winnicki</surname><given-names>SM</given-names></name><name><surname>Wohl</surname><given-names>S</given-names></name><name><surname>Wölfel</surname><given-names>R</given-names></name><name><surname>Yozwiak</surname><given-names>NL</given-names></name><name><surname>Andersen</surname><given-names>KG</given-names></name><name><surname>Blyden</surname><given-names>SO</given-names></name><name><surname>Bolay</surname><given-names>F</given-names></name><name><surname>Carroll</surname><given-names>MW</given-names></name><name><surname>Dahn</surname><given-names>B</given-names></name><name><surname>Diallo</surname><given-names>B</given-names></name><name><surname>Formenty</surname><given-names>P</given-names></name><name><surname>Fraser</surname><given-names>C</given-names></name><name><surname>Gao</surname><given-names>GF</given-names></name><name><surname>Garry</surname><given-names>RF</given-names></name><name><surname>Goodfellow</surname><given-names>I</given-names></name><name><surname>Günther</surname><given-names>S</given-names></name><name><surname>Happi</surname><given-names>CT</given-names></name><name><surname>Holmes</surname><given-names>EC</given-names></name><name><surname>Kargbo</surname><given-names>B</given-names></name><name><surname>Keïta</surname><given-names>S</given-names></name><name><surname>Kellam</surname><given-names>P</given-names></name><name><surname>Koopmans</surname><given-names>MPG</given-names></name><name><surname>Kuhn</surname><given-names>JH</given-names></name><name><surname>Loman</surname><given-names>NJ</given-names></name><name><surname>Magassouba</surname><given-names>N</given-names></name><name><surname>Naidoo</surname><given-names>D</given-names></name><name><surname>Nichol</surname><given-names>ST</given-names></name><name><surname>Nyenswah</surname><given-names>T</given-names></name><name><surname>Palacios</surname><given-names>G</given-names></name><name><surname>Pybus</surname><given-names>OG</given-names></name><name><surname>Sabeti</surname><given-names>PC</given-names></name><name><surname>Sall</surname><given-names>A</given-names></name><name><surname>Ströher</surname><given-names>U</given-names></name><name><surname>Wurie</surname><given-names>I</given-names></name><name><surname>Suchard</surname><given-names>MA</given-names></name><name><surname>Lemey</surname><given-names>P</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name></person-group><year>2017</year><article-title>Virus genomes reveal factors that spread and sustained the Ebola epidemic</article-title><source>Nature</source><volume>544</volume><fpage>309</fpage><lpage>315</lpage><pub-id pub-id-type="doi">10.1038/nature22040</pub-id><pub-id pub-id-type="pmid">28405027</pub-id></element-citation></ref><ref id="bib31"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Dudas</surname><given-names>G</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name></person-group><year>2016</year><article-title>MERS-CoV recombination: implications about the reservoir and potential for adaptation</article-title><source>Virus Evolution</source><volume>2</volume><elocation-id>vev023</elocation-id><pub-id pub-id-type="doi">10.1093/ve/vev023</pub-id><pub-id pub-id-type="pmid">27774293</pub-id></element-citation></ref><ref id="bib32"><element-citation publication-type="book"><person-group person-group-type="author"><name><surname>Dudas</surname><given-names>G</given-names></name></person-group><year>2017</year><data-title>mers-structure: Looking into MERS-CoV dynamics through the structured coalescent lens</data-title><publisher-name>Bedford Lab</publisher-name><ext-link ext-link-type="uri" xlink:href="https://github.com/blab/mers-structure">https://github.com/blab/mers-structure</ext-link></element-citation></ref><ref id="bib33"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Fagbo</surname><given-names>SF</given-names></name><name><surname>Skakni</surname><given-names>L</given-names></name><name><surname>Chu</surname><given-names>DK</given-names></name><name><surname>Garbati</surname><given-names>MA</given-names></name><name><surname>Joseph</surname><given-names>M</given-names></name><name><surname>Peiris</surname><given-names>M</given-names></name><name><surname>Hakawi</surname><given-names>AM</given-names></name></person-group><year>2015</year><article-title>Molecular epidemiology of hospital outbreak of Middle East respiratory syndrome, Riyadh, Saudi Arabia, 2014</article-title><source>Emerging Infectious Diseases</source><volume>21</volume><fpage>1981</fpage><lpage>1988</lpage><pub-id pub-id-type="doi">10.3201/eid2111.150944</pub-id><pub-id pub-id-type="pmid">26484549</pub-id></element-citation></ref><ref id="bib34"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Faria</surname><given-names>NR</given-names></name><name><surname>Suchard</surname><given-names>MA</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name><name><surname>Streicker</surname><given-names>DG</given-names></name><name><surname>Lemey</surname><given-names>P</given-names></name></person-group><year>2013</year><article-title>Simultaneously reconstructing viral cross-species transmission history and identifying the underlying constraints</article-title><source>Philosophical Transactions of the Royal Society B: Biological Sciences</source><volume>368</volume><elocation-id>20120196</elocation-id><pub-id pub-id-type="doi">10.1098/rstb.2012.0196</pub-id><pub-id pub-id-type="pmid">23382420</pub-id></element-citation></ref><ref id="bib35"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Frost</surname><given-names>SD</given-names></name><name><surname>Volz</surname><given-names>EM</given-names></name></person-group><year>2010</year><article-title>Viral phylodynamics and the search for an 'effective number of infections'</article-title><source>Philosophical Transactions of the Royal Society B: Biological Sciences</source><volume>365</volume><fpage>1879</fpage><lpage>1890</lpage><pub-id pub-id-type="doi">10.1098/rstb.2010.0060</pub-id><pub-id pub-id-type="pmid">20478883</pub-id></element-citation></ref><ref id="bib36"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Gill</surname><given-names>MS</given-names></name><name><surname>Lemey</surname><given-names>P</given-names></name><name><surname>Faria</surname><given-names>NR</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name><name><surname>Shapiro</surname><given-names>B</given-names></name><name><surname>Suchard</surname><given-names>MA</given-names></name></person-group><year>2013</year><article-title>Improving Bayesian population dynamics inference: a coalescent-based model for multiple loci</article-title><source>Molecular Biology and Evolution</source><volume>30</volume><elocation-id>713</elocation-id><lpage>724</lpage><pub-id pub-id-type="doi">10.1093/molbev/mss265</pub-id><pub-id pub-id-type="pmid">23180580</pub-id></element-citation></ref><ref id="bib37"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Gire</surname><given-names>SK</given-names></name><name><surname>Goba</surname><given-names>A</given-names></name><name><surname>Andersen</surname><given-names>KG</given-names></name><name><surname>Sealfon</surname><given-names>RS</given-names></name><name><surname>Park</surname><given-names>DJ</given-names></name><name><surname>Kanneh</surname><given-names>L</given-names></name><name><surname>Jalloh</surname><given-names>S</given-names></name><name><surname>Momoh</surname><given-names>M</given-names></name><name><surname>Fullah</surname><given-names>M</given-names></name><name><surname>Dudas</surname><given-names>G</given-names></name><name><surname>Wohl</surname><given-names>S</given-names></name><name><surname>Moses</surname><given-names>LM</given-names></name><name><surname>Yozwiak</surname><given-names>NL</given-names></name><name><surname>Winnicki</surname><given-names>S</given-names></name><name><surname>Matranga</surname><given-names>CB</given-names></name><name><surname>Malboeuf</surname><given-names>CM</given-names></name><name><surname>Qu</surname><given-names>J</given-names></name><name><surname>Gladden</surname><given-names>AD</given-names></name><name><surname>Schaffner</surname><given-names>SF</given-names></name><name><surname>Yang</surname><given-names>X</given-names></name><name><surname>Jiang</surname><given-names>PP</given-names></name><name><surname>Nekoui</surname><given-names>M</given-names></name><name><surname>Colubri</surname><given-names>A</given-names></name><name><surname>Coomber</surname><given-names>MR</given-names></name><name><surname>Fonnie</surname><given-names>M</given-names></name><name><surname>Moigboi</surname><given-names>A</given-names></name><name><surname>Gbakie</surname><given-names>M</given-names></name><name><surname>Kamara</surname><given-names>FK</given-names></name><name><surname>Tucker</surname><given-names>V</given-names></name><name><surname>Konuwa</surname><given-names>E</given-names></name><name><surname>Saffa</surname><given-names>S</given-names></name><name><surname>Sellu</surname><given-names>J</given-names></name><name><surname>Jalloh</surname><given-names>AA</given-names></name><name><surname>Kovoma</surname><given-names>A</given-names></name><name><surname>Koninga</surname><given-names>J</given-names></name><name><surname>Mustapha</surname><given-names>I</given-names></name><name><surname>Kargbo</surname><given-names>K</given-names></name><name><surname>Foday</surname><given-names>M</given-names></name><name><surname>Yillah</surname><given-names>M</given-names></name><name><surname>Kanneh</surname><given-names>F</given-names></name><name><surname>Robert</surname><given-names>W</given-names></name><name><surname>Massally</surname><given-names>JL</given-names></name><name><surname>Chapman</surname><given-names>SB</given-names></name><name><surname>Bochicchio</surname><given-names>J</given-names></name><name><surname>Murphy</surname><given-names>C</given-names></name><name><surname>Nusbaum</surname><given-names>C</given-names></name><name><surname>Young</surname><given-names>S</given-names></name><name><surname>Birren</surname><given-names>BW</given-names></name><name><surname>Grant</surname><given-names>DS</given-names></name><name><surname>Scheiffelin</surname><given-names>JS</given-names></name><name><surname>Lander</surname><given-names>ES</given-names></name><name><surname>Happi</surname><given-names>C</given-names></name><name><surname>Gevao</surname><given-names>SM</given-names></name><name><surname>Gnirke</surname><given-names>A</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name><name><surname>Garry</surname><given-names>RF</given-names></name><name><surname>Khan</surname><given-names>SH</given-names></name><name><surname>Sabeti</surname><given-names>PC</given-names></name></person-group><year>2014</year><article-title>Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak</article-title><source>Science</source><volume>345</volume><fpage>1369</fpage><lpage>1372</lpage><pub-id pub-id-type="doi">10.1126/science.1259657</pub-id><pub-id pub-id-type="pmid">25214632</pub-id></element-citation></ref><ref id="bib38"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Grubaugh</surname><given-names>ND</given-names></name><name><surname>Ladner</surname><given-names>JT</given-names></name><name><surname>Kraemer</surname><given-names>MUG</given-names></name><name><surname>Dudas</surname><given-names>G</given-names></name><name><surname>Tan</surname><given-names>AL</given-names></name><name><surname>Gangavarapu</surname><given-names>K</given-names></name><name><surname>Wiley</surname><given-names>MR</given-names></name><name><surname>White</surname><given-names>S</given-names></name><name><surname>Thézé</surname><given-names>J</given-names></name><name><surname>Magnani</surname><given-names>DM</given-names></name><name><surname>Prieto</surname><given-names>K</given-names></name><name><surname>Reyes</surname><given-names>D</given-names></name><name><surname>Bingham</surname><given-names>AM</given-names></name><name><surname>Paul</surname><given-names>LM</given-names></name><name><surname>Robles-Sikisaka</surname><given-names>R</given-names></name><name><surname>Oliveira</surname><given-names>G</given-names></name><name><surname>Pronty</surname><given-names>D</given-names></name><name><surname>Barcellona</surname><given-names>CM</given-names></name><name><surname>Metsky</surname><given-names>HC</given-names></name><name><surname>Baniecki</surname><given-names>ML</given-names></name><name><surname>Barnes</surname><given-names>KG</given-names></name><name><surname>Chak</surname><given-names>B</given-names></name><name><surname>Freije</surname><given-names>CA</given-names></name><name><surname>Gladden-Young</surname><given-names>A</given-names></name><name><surname>Gnirke</surname><given-names>A</given-names></name><name><surname>Luo</surname><given-names>C</given-names></name><name><surname>MacInnis</surname><given-names>B</given-names></name><name><surname>Matranga</surname><given-names>CB</given-names></name><name><surname>Park</surname><given-names>DJ</given-names></name><name><surname>Qu</surname><given-names>J</given-names></name><name><surname>Schaffner</surname><given-names>SF</given-names></name><name><surname>Tomkins-Tinch</surname><given-names>C</given-names></name><name><surname>West</surname><given-names>KL</given-names></name><name><surname>Winnicki</surname><given-names>SM</given-names></name><name><surname>Wohl</surname><given-names>S</given-names></name><name><surname>Yozwiak</surname><given-names>NL</given-names></name><name><surname>Quick</surname><given-names>J</given-names></name><name><surname>Fauver</surname><given-names>JR</given-names></name><name><surname>Khan</surname><given-names>K</given-names></name><name><surname>Brent</surname><given-names>SE</given-names></name><name><surname>Reiner</surname><given-names>RC</given-names></name><name><surname>Lichtenberger</surname><given-names>PN</given-names></name><name><surname>Ricciardi</surname><given-names>MJ</given-names></name><name><surname>Bailey</surname><given-names>VK</given-names></name><name><surname>Watkins</surname><given-names>DI</given-names></name><name><surname>Cone</surname><given-names>MR</given-names></name><name><surname>Kopp</surname><given-names>EW</given-names></name><name><surname>Hogan</surname><given-names>KN</given-names></name><name><surname>Cannons</surname><given-names>AC</given-names></name><name><surname>Jean</surname><given-names>R</given-names></name><name><surname>Monaghan</surname><given-names>AJ</given-names></name><name><surname>Garry</surname><given-names>RF</given-names></name><name><surname>Loman</surname><given-names>NJ</given-names></name><name><surname>Faria</surname><given-names>NR</given-names></name><name><surname>Porcelli</surname><given-names>MC</given-names></name><name><surname>Vasquez</surname><given-names>C</given-names></name><name><surname>Nagle</surname><given-names>ER</given-names></name><name><surname>Cummings</surname><given-names>DAT</given-names></name><name><surname>Stanek</surname><given-names>D</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name><name><surname>Sanchez-Lockhart</surname><given-names>M</given-names></name><name><surname>Sabeti</surname><given-names>PC</given-names></name><name><surname>Gillis</surname><given-names>LD</given-names></name><name><surname>Michael</surname><given-names>SF</given-names></name><name><surname>Bedford</surname><given-names>T</given-names></name><name><surname>Pybus</surname><given-names>OG</given-names></name><name><surname>Isern</surname><given-names>S</given-names></name><name><surname>Palacios</surname><given-names>G</given-names></name><name><surname>Andersen</surname><given-names>KG</given-names></name></person-group><year>2017</year><article-title>Genomic epidemiology reveals multiple introductions of Zika virus into the United States</article-title><source>Nature</source><volume>546</volume><fpage>401</fpage><lpage>405</lpage><pub-id pub-id-type="doi">10.1038/nature22400</pub-id><pub-id pub-id-type="pmid">28538723</pub-id></element-citation></ref><ref id="bib39"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Guindon</surname><given-names>S</given-names></name><name><surname>Gascuel</surname><given-names>O</given-names></name><name><surname>A Simple</surname><given-names>RB</given-names></name></person-group><year>2003</year><article-title>A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood</article-title><source>Systematic Biology</source><volume>52</volume><fpage>696</fpage><lpage>704</lpage><pub-id pub-id-type="doi">10.1080/10635150390235520</pub-id><pub-id pub-id-type="pmid">14530136</pub-id></element-citation></ref><ref id="bib40"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Haagmans</surname><given-names>BL</given-names></name><name><surname>Al Dhahiry</surname><given-names>SH</given-names></name><name><surname>Reusken</surname><given-names>CB</given-names></name><name><surname>Raj</surname><given-names>VS</given-names></name><name><surname>Galiano</surname><given-names>M</given-names></name><name><surname>Myers</surname><given-names>R</given-names></name><name><surname>Godeke</surname><given-names>GJ</given-names></name><name><surname>Jonges</surname><given-names>M</given-names></name><name><surname>Farag</surname><given-names>E</given-names></name><name><surname>Diab</surname><given-names>A</given-names></name><name><surname>Ghobashy</surname><given-names>H</given-names></name><name><surname>Alhajri</surname><given-names>F</given-names></name><name><surname>Al-Thani</surname><given-names>M</given-names></name><name><surname>Al-Marri</surname><given-names>SA</given-names></name><name><surname>Al Romaihi</surname><given-names>HE</given-names></name><name><surname>Al Khal</surname><given-names>A</given-names></name><name><surname>Bermingham</surname><given-names>A</given-names></name><name><surname>Osterhaus</surname><given-names>AD</given-names></name><name><surname>AlHajri</surname><given-names>MM</given-names></name><name><surname>Koopmans</surname><given-names>MP</given-names></name></person-group><year>2014</year><article-title>Middle East respiratory syndrome coronavirus in dromedary camels: an outbreak investigation</article-title><source>The Lancet Infectious Diseases</source><volume>14</volume><fpage>140</fpage><lpage>145</lpage><pub-id pub-id-type="doi">10.1016/S1473-3099(13)70690-X</pub-id><pub-id pub-id-type="pmid">24355866</pub-id></element-citation></ref><ref id="bib41"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Hasegawa</surname><given-names>M</given-names></name><name><surname>Kishino</surname><given-names>H</given-names></name><name><surname>Yano</surname><given-names>T</given-names></name><name><surname>Ta</surname><given-names>Y</given-names></name></person-group><year>1985</year><article-title>Dating of the human-ape splitting by a molecular clock of mitochondrial DNA</article-title><source>Journal of Molecular Evolution</source><volume>22</volume><fpage>160</fpage><lpage>174</lpage><pub-id pub-id-type="doi">10.1007/BF02101694</pub-id><pub-id pub-id-type="pmid">3934395</pub-id></element-citation></ref><ref id="bib42"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Heled</surname><given-names>J</given-names></name><name><surname>Bouckaert</surname><given-names>RR</given-names></name></person-group><year>2013</year><article-title>Looking for trees in the forest: summary tree from posterior samples</article-title><source>BMC Evolutionary Biology</source><volume>13</volume><elocation-id>221</elocation-id><pub-id pub-id-type="doi">10.1186/1471-2148-13-221</pub-id><pub-id pub-id-type="pmid">24093883</pub-id></element-citation></ref><ref id="bib43"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Hemida</surname><given-names>MG</given-names></name><name><surname>Chu</surname><given-names>DK</given-names></name><name><surname>Poon</surname><given-names>LL</given-names></name><name><surname>Perera</surname><given-names>RA</given-names></name><name><surname>Alhammadi</surname><given-names>MA</given-names></name><name><surname>Ng</surname><given-names>HY</given-names></name><name><surname>Siu</surname><given-names>LY</given-names></name><name><surname>Guan</surname><given-names>Y</given-names></name><name><surname>Alnaeem</surname><given-names>A</given-names></name><name><surname>Peiris</surname><given-names>M</given-names></name></person-group><year>2014</year><article-title>MERS coronavirus in dromedary camel herd, Saudi Arabia</article-title><source>Emerging Infectious Diseases</source><volume>20</volume><pub-id pub-id-type="doi">10.3201/eid2007.140571</pub-id><pub-id pub-id-type="pmid">24964193</pub-id></element-citation></ref><ref id="bib44"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Herrewegh</surname><given-names>AA</given-names></name><name><surname>Smeenk</surname><given-names>I</given-names></name><name><surname>Horzinek</surname><given-names>MC</given-names></name><name><surname>Rottier</surname><given-names>PJ</given-names></name><name><surname>de Groot</surname><given-names>RJ</given-names></name></person-group><year>1998</year><article-title>Feline coronavirus type II strains 79-1683 and 79-1146 originate from a double recombination between feline coronavirus type I and canine coronavirus</article-title><source>Journal of Virology</source><volume>72</volume><fpage>4508</fpage><lpage>4514</lpage><pub-id pub-id-type="pmid">9557750</pub-id></element-citation></ref><ref id="bib45"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Hon</surname><given-names>CC</given-names></name><name><surname>Lam</surname><given-names>TY</given-names></name><name><surname>Shi</surname><given-names>ZL</given-names></name><name><surname>Drummond</surname><given-names>AJ</given-names></name><name><surname>Yip</surname><given-names>CW</given-names></name><name><surname>Zeng</surname><given-names>F</given-names></name><name><surname>Lam</surname><given-names>PY</given-names></name><name><surname>Leung</surname><given-names>FC</given-names></name></person-group><year>2008</year><article-title>Evidence of the recombinant origin of a bat severe acute respiratory syndrome (SARS)-like coronavirus and its implications on the direct ancestor of SARS coronavirus</article-title><source>Journal of Virology</source><volume>82</volume><fpage>1819</fpage><lpage>1826</lpage><pub-id pub-id-type="doi">10.1128/JVI.01926-07</pub-id><pub-id pub-id-type="pmid">18057240</pub-id></element-citation></ref><ref id="bib46"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Hunter</surname><given-names>JC</given-names></name><name><surname>Nguyen</surname><given-names>D</given-names></name><name><surname>Aden</surname><given-names>B</given-names></name><name><surname>Al Bandar</surname><given-names>Z</given-names></name><name><surname>Al Dhaheri</surname><given-names>W</given-names></name><name><surname>Abu Elkheir</surname><given-names>K</given-names></name><name><surname>Khudair</surname><given-names>A</given-names></name><name><surname>Al Mulla</surname><given-names>M</given-names></name><name><surname>El Saleh</surname><given-names>F</given-names></name><name><surname>Imambaccus</surname><given-names>H</given-names></name><name><surname>Al Kaabi</surname><given-names>N</given-names></name><name><surname>Sheikh</surname><given-names>FA</given-names></name><name><surname>Sasse</surname><given-names>J</given-names></name><name><surname>Turner</surname><given-names>A</given-names></name><name><surname>Abdel Wareth</surname><given-names>L</given-names></name><name><surname>Weber</surname><given-names>S</given-names></name><name><surname>Al Ameri</surname><given-names>A</given-names></name><name><surname>Abu Amer</surname><given-names>W</given-names></name><name><surname>Alami</surname><given-names>NN</given-names></name><name><surname>Bunga</surname><given-names>S</given-names></name><name><surname>Haynes</surname><given-names>LM</given-names></name><name><surname>Hall</surname><given-names>AJ</given-names></name><name><surname>Kallen</surname><given-names>AJ</given-names></name><name><surname>Kuhar</surname><given-names>D</given-names></name><name><surname>Pham</surname><given-names>H</given-names></name><name><surname>Pringle</surname><given-names>K</given-names></name><name><surname>Tong</surname><given-names>S</given-names></name><name><surname>Whitaker</surname><given-names>BL</given-names></name><name><surname>Gerber</surname><given-names>SI</given-names></name><name><surname>Al Hosani</surname><given-names>FI</given-names></name></person-group><year>2016</year><article-title>Transmission of Middle East Respiratory Syndrome Coronavirus Infections in Healthcare Settings, Abu Dhabi</article-title><source>Emerging Infectious Diseases</source><volume>22</volume><fpage>647</fpage><lpage>656</lpage><pub-id pub-id-type="doi">10.3201/eid2204.151615</pub-id><pub-id pub-id-type="pmid">26981708</pub-id></element-citation></ref><ref id="bib47"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kandeil</surname><given-names>A</given-names></name><name><surname>Shehata</surname><given-names>MM</given-names></name><name><surname>El Shesheny</surname><given-names>R</given-names></name><name><surname>Gomaa</surname><given-names>MR</given-names></name><name><surname>Ali</surname><given-names>MA</given-names></name><name><surname>Kayali</surname><given-names>G</given-names></name></person-group><year>2016</year><article-title>Complete Genome Sequence of Middle East Respiratory Syndrome Coronavirus Isolated from a Dromedary Camel in Egypt</article-title><source>Genome Announcements</source><volume>4</volume><fpage>e00309-16</fpage><pub-id pub-id-type="doi">10.1128/genomeA.00309-16</pub-id><pub-id pub-id-type="pmid">27125484</pub-id></element-citation></ref><ref id="bib48"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kapoor</surname><given-names>M</given-names></name><name><surname>Pringle</surname><given-names>K</given-names></name><name><surname>Kumar</surname><given-names>A</given-names></name><name><surname>Dearth</surname><given-names>S</given-names></name><name><surname>Liu</surname><given-names>L</given-names></name><name><surname>Lovchik</surname><given-names>J</given-names></name><name><surname>Perez</surname><given-names>O</given-names></name><name><surname>Pontones</surname><given-names>P</given-names></name><name><surname>Richards</surname><given-names>S</given-names></name><name><surname>Yeadon-Fagbohun</surname><given-names>J</given-names></name><name><surname>Breakwell</surname><given-names>L</given-names></name><name><surname>Chea</surname><given-names>N</given-names></name><name><surname>Cohen</surname><given-names>NJ</given-names></name><name><surname>Schneider</surname><given-names>E</given-names></name><name><surname>Erdman</surname><given-names>D</given-names></name><name><surname>Haynes</surname><given-names>L</given-names></name><name><surname>Pallansch</surname><given-names>M</given-names></name><name><surname>Tao</surname><given-names>Y</given-names></name><name><surname>Tong</surname><given-names>S</given-names></name><name><surname>Gerber</surname><given-names>S</given-names></name><name><surname>Swerdlow</surname><given-names>D</given-names></name><name><surname>Feikin</surname><given-names>DR</given-names></name></person-group><year>2014</year><article-title>Clinical and laboratory findings of the first imported case of Middle East respiratory syndrome coronavirus to the United States</article-title><source>Clinical Infectious Diseases</source><volume>59</volume><fpage>1511</fpage><lpage>1518</lpage><pub-id pub-id-type="doi">10.1093/cid/ciu635</pub-id><pub-id pub-id-type="pmid">25100864</pub-id></element-citation></ref><ref id="bib49"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Katoh</surname><given-names>K</given-names></name><name><surname>Standley</surname><given-names>DM</given-names></name></person-group><year>2013</year><article-title>MAFFT multiple sequence alignment software version 7: improvements in performance and usability</article-title><source>Molecular Biology and Evolution</source><volume>30</volume><fpage>772</fpage><lpage>780</lpage><pub-id pub-id-type="doi">10.1093/molbev/mst010</pub-id><pub-id pub-id-type="pmid">23329690</pub-id></element-citation></ref><ref id="bib50"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Keck</surname><given-names>JG</given-names></name><name><surname>Matsushima</surname><given-names>GK</given-names></name><name><surname>Makino</surname><given-names>S</given-names></name><name><surname>Fleming</surname><given-names>JO</given-names></name><name><surname>Vannier</surname><given-names>DM</given-names></name><name><surname>Stohlman</surname><given-names>SA</given-names></name><name><surname>Lai</surname><given-names>MM</given-names></name></person-group><year>1988</year><article-title>In vivo RNA-RNA recombination of coronavirus in mouse brain</article-title><source>Journal of Virology</source><volume>62</volume><fpage>1810</fpage><lpage>1813</lpage><pub-id pub-id-type="pmid">2833625</pub-id></element-citation></ref><ref id="bib51"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kim</surname><given-names>Y</given-names></name><name><surname>Cheon</surname><given-names>S</given-names></name><name><surname>Min</surname><given-names>CK</given-names></name><name><surname>Sohn</surname><given-names>KM</given-names></name><name><surname>Kang</surname><given-names>YJ</given-names></name><name><surname>Cha</surname><given-names>YJ</given-names></name><name><surname>Kang</surname><given-names>JI</given-names></name><name><surname>Han</surname><given-names>SK</given-names></name><name><surname>Ha</surname><given-names>NY</given-names></name><name><surname>Kim</surname><given-names>G</given-names></name><name><surname>Aigerim</surname><given-names>A</given-names></name><name><surname>Shin</surname><given-names>HM</given-names></name><name><surname>Choi</surname><given-names>MS</given-names></name><name><surname>Kim</surname><given-names>S</given-names></name><name><surname>Cho</surname><given-names>HS</given-names></name><name><surname>Kim</surname><given-names>YS</given-names></name><name><surname>Cho</surname><given-names>NH</given-names></name></person-group><year>2016</year><article-title>Spread of Mutant Middle East Respiratory Syndrome Coronavirus with Reduced Affinity to Human CD26 during the South Korean Outbreak</article-title><source>mBio</source><volume>7</volume><fpage>e00019-16</fpage><pub-id pub-id-type="doi">10.1128/mBio.00019-16</pub-id><pub-id pub-id-type="pmid">26933050</pub-id></element-citation></ref><ref id="bib52"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kim</surname><given-names>YJ</given-names></name><name><surname>Cho</surname><given-names>YJ</given-names></name><name><surname>Kim</surname><given-names>DW</given-names></name><name><surname>Yang</surname><given-names>JS</given-names></name><name><surname>Kim</surname><given-names>H</given-names></name><name><surname>Park</surname><given-names>S</given-names></name><name><surname>Han</surname><given-names>YW</given-names></name><name><surname>Yun</surname><given-names>MR</given-names></name><name><surname>Lee</surname><given-names>HS</given-names></name><name><surname>Kim</surname><given-names>AR</given-names></name><name><surname>Heo</surname><given-names>DR</given-names></name><name><surname>Kim</surname><given-names>JA</given-names></name><name><surname>Kim</surname><given-names>SJ</given-names></name><name><surname>Jung</surname><given-names>HD</given-names></name><name><surname>Kim</surname><given-names>N</given-names></name><name><surname>Yoon</surname><given-names>SH</given-names></name><name><surname>Nam</surname><given-names>JG</given-names></name><name><surname>Kang</surname><given-names>HJ</given-names></name><name><surname>Cheong</surname><given-names>HM</given-names></name><name><surname>Lee</surname><given-names>JS</given-names></name><name><surname>Chun</surname><given-names>J</given-names></name><name><surname>Kim</surname><given-names>SS</given-names></name></person-group><year>2015</year><article-title>Complete Genome Sequence of Middle East Respiratory Syndrome Coronavirus KOR/KNIH/002_05_2015, Isolated in South Korea</article-title><source>Genome Announcements</source><volume>3</volume><fpage>e00787-15</fpage><pub-id pub-id-type="doi">10.1128/genomeA.00787-15</pub-id><pub-id pub-id-type="pmid">26272558</pub-id></element-citation></ref><ref id="bib53"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kosakovsky Pond</surname><given-names>SL</given-names></name><name><surname>Posada</surname><given-names>D</given-names></name><name><surname>Gravenor</surname><given-names>MB</given-names></name><name><surname>Woelk</surname><given-names>CH</given-names></name><name><surname>Frost</surname><given-names>SD</given-names></name></person-group><year>2006</year><article-title>GARD: a genetic algorithm for recombination detection</article-title><source>Bioinformatics</source><volume>22</volume><fpage>3096</fpage><lpage>3098</lpage><pub-id pub-id-type="doi">10.1093/bioinformatics/btl474</pub-id><pub-id pub-id-type="pmid">17110367</pub-id></element-citation></ref><ref id="bib54"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kottier</surname><given-names>SA</given-names></name><name><surname>Cavanagh</surname><given-names>D</given-names></name><name><surname>Britton</surname><given-names>P</given-names></name></person-group><year>1995</year><article-title>Experimental evidence of recombination in coronavirus infectious bronchitis virus</article-title><source>Virology</source><volume>213</volume><fpage>569</fpage><lpage>580</lpage><pub-id pub-id-type="doi">10.1006/viro.1995.0029</pub-id><pub-id pub-id-type="pmid">7491781</pub-id></element-citation></ref><ref id="bib55"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kühnert</surname><given-names>D</given-names></name><name><surname>Stadler</surname><given-names>T</given-names></name><name><surname>Vaughan</surname><given-names>TG</given-names></name><name><surname>Drummond</surname><given-names>AJ</given-names></name></person-group><year>2016</year><article-title>Phylodynamics with migration: A computational framework to quantify population structure from genomic data</article-title><source>Molecular Biology and Evolution</source><volume>33</volume><fpage>2102</fpage><lpage>2116</lpage><pub-id pub-id-type="doi">10.1093/molbev/msw064</pub-id><pub-id pub-id-type="pmid">27189573</pub-id></element-citation></ref><ref id="bib56"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lai</surname><given-names>MM</given-names></name><name><surname>Baric</surname><given-names>RS</given-names></name><name><surname>Makino</surname><given-names>S</given-names></name><name><surname>Keck</surname><given-names>JG</given-names></name><name><surname>Egbert</surname><given-names>J</given-names></name><name><surname>Leibowitz</surname><given-names>JL</given-names></name><name><surname>Stohlman</surname><given-names>SA</given-names></name></person-group><year>1985</year><article-title>Recombination between nonsegmented RNA genomes of murine coronaviruses</article-title><source>Journal of Virology</source><volume>56</volume><fpage>449</fpage><lpage>456</lpage><pub-id pub-id-type="pmid">2997467</pub-id></element-citation></ref><ref id="bib57"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lamers</surname><given-names>MM</given-names></name><name><surname>Raj</surname><given-names>VS</given-names></name><name><surname>Shafei</surname><given-names>M</given-names></name><name><surname>Ali</surname><given-names>SS</given-names></name><name><surname>Abdallh</surname><given-names>SM</given-names></name><name><surname>Gazo</surname><given-names>M</given-names></name><name><surname>Nofal</surname><given-names>S</given-names></name><name><surname>Lu</surname><given-names>X</given-names></name><name><surname>Erdman</surname><given-names>DD</given-names></name><name><surname>Koopmans</surname><given-names>MP</given-names></name><name><surname>Abdallat</surname><given-names>M</given-names></name><name><surname>Haddadin</surname><given-names>A</given-names></name><name><surname>Haagmans</surname><given-names>BL</given-names></name></person-group><year>2016</year><article-title>Deletion Variants of Middle East Respiratory Syndrome Coronavirus from Humans, Jordan, 2015</article-title><source>Emerging Infectious Diseases</source><volume>22</volume><fpage>716</fpage><lpage>719</lpage><pub-id pub-id-type="doi">10.3201/eid2204.152065</pub-id><pub-id pub-id-type="pmid">26981770</pub-id></element-citation></ref><ref id="bib58"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lau</surname><given-names>SK</given-names></name><name><surname>Wernery</surname><given-names>R</given-names></name><name><surname>Wong</surname><given-names>EY</given-names></name><name><surname>Joseph</surname><given-names>S</given-names></name><name><surname>Tsang</surname><given-names>AK</given-names></name><name><surname>Patteril</surname><given-names>NA</given-names></name><name><surname>Elizabeth</surname><given-names>SK</given-names></name><name><surname>Chan</surname><given-names>KH</given-names></name><name><surname>Muhammed</surname><given-names>R</given-names></name><name><surname>Kinne</surname><given-names>J</given-names></name><name><surname>Yuen</surname><given-names>KY</given-names></name><name><surname>Wernery</surname><given-names>U</given-names></name><name><surname>Woo</surname><given-names>PC</given-names></name></person-group><year>2016</year><article-title>Polyphyletic origin of MERS coronaviruses and isolation of a novel clade A strain from dromedary camels in the United Arab Emirates</article-title><source>Emerging Microbes & Infections</source><volume>5</volume><elocation-id>e128</elocation-id><pub-id pub-id-type="doi">10.1038/emi.2016.129</pub-id><pub-id pub-id-type="pmid">27999424</pub-id></element-citation></ref><ref id="bib59"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lemey</surname><given-names>P</given-names></name><name><surname>Rambaut</surname><given-names>A</given-names></name><name><surname>Drummond</surname><given-names>AJ</given-names></name><name><surname>Suchard</surname><given-names>MA</given-names></name></person-group><year>2009</year><article-title>Bayesian phylogeography finds its roots</article-title><source>PLoS Computational Biology</source><volume>5</volume><elocation-id>e1000520</elocation-id><pub-id pub-id-type="doi">10.1371/journal.pcbi.1000520</pub-id><pub-id pub-id-type="pmid">19779555</pub-id></element-citation></ref><ref id="bib60"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lipsitch</surname><given-names>M</given-names></name><name><surname>Barclay</surname><given-names>W</given-names></name><name><surname>Raman</surname><given-names>R</given-names></name><name><surname>Russell</surname><given-names>CJ</given-names></name><name><surname>Belser</surname><given-names>JA</given-names></name><name><surname>Cobey</surname><given-names>S</given-names></name><name><surname>Kasson</surname><given-names>PM</given-names></name><name><surname>Lloyd-Smith</surname><given-names>JO</given-names></name><name><surname>Maurer-Stroh</surname><given-names>S</given-names></name><name><surname>Riley</surname><given-names>S</given-names></name><name><surname>Beauchemin</surname><given-names>CA</given-names></name><name><surname>Bedford</surname><given-names>T</given-names></name><name><surname>Friedrich</surname><given-names>TC</given-names></name><name><surname>Handel</surname><given-names>A</given-names></name><name><surname>Herfst</surname><given-names>S</given-names></name><name><surname>Murcia</surname><given-names>PR</given-names></name><name><surname>Roche</surname><given-names>B</given-names></name><name><surname>Wilke</surname><given-names>CO</given-names></name><name><surname>Russell</surname><given-names>CA</given-names></name></person-group><year>2016</year><article-title>Viral factors in influenza pandemic risk assessment</article-title><source>eLife</source><volume>5</volume><elocation-id>e18491</elocation-id><pub-id pub-id-type="doi">10.7554/eLife.18491</pub-id><pub-id pub-id-type="pmid">27834632</pub-id></element-citation></ref><ref id="bib61"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Liu</surname><given-names>D</given-names></name><name><surname>Shi</surname><given-names>W</given-names></name><name><surname>Shi</surname><given-names>Y</given-names></name><name><surname>Wang</surname><given-names>D</given-names></name><name><surname>Xiao</surname><given-names>H</given-names></name><name><surname>Li</surname><given-names>W</given-names></name><name><surname>Bi</surname><given-names>Y</given-names></name><name><surname>Wu</surname><given-names>Y</given-names></name><name><surname>Li</surname><given-names>X</given-names></name><name><surname>Yan</surname><given-names>J</given-names></name><name><surname>Liu</surname><given-names>W</given-names></name><name><surname>Zhao</surname><given-names>G</given-names></name><name><surname>Yang</surname><given-names>W</given-names></name><name><surname>Wang</surname><given-names>Y</given-names></name><name><surname>Ma</surname><given-names>J</given-names></name><name><surname>Shu</surname><given-names>Y</given-names></name><name><surname>Lei</surname><given-names>F</given-names></name><name><surname>Gao</surname><given-names>GF</given-names></name></person-group><year>2013</year><article-title>Origin and diversity of novel avian influenza A H7N9 viruses causing human infection: phylogenetic, structural, and coalescent analyses</article-title><source>The Lancet</source><volume>381</volume><fpage>1926</fpage><lpage>1932</lpage><pub-id pub-id-type="doi">10.1016/S0140-6736(13)60938-1</pub-id><pub-id pub-id-type="pmid">23643111</pub-id></element-citation></ref><ref id="bib62"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lloyd-Smith</surname><given-names>JO</given-names></name><name><surname>Schreiber</surname><given-names>SJ</given-names></name><name><surname>Kopp</surname><given-names>PE</given-names></name><name><surname>Getz</surname><given-names>WM</given-names></name></person-group><year>2005</year><article-title>Superspreading and the effect of individual variation on disease emergence</article-title><source>Nature</source><volume>438</volume><fpage>355</fpage><lpage>359</lpage><pub-id pub-id-type="doi">10.1038/nature04153</pub-id><pub-id pub-id-type="pmid">16292310</pub-id></element-citation></ref><ref id="bib63"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lu</surname><given-names>X</given-names></name><name><surname>Rowe</surname><given-names>LA</given-names></name><name><surname>Frace</surname><given-names>M</given-names></name><name><surname>Stevens</surname><given-names>J</given-names></name><name><surname>Abedi</surname><given-names>GR</given-names></name><name><surname>Elnile</surname><given-names>O</given-names></name><name><surname>Banassir</surname><given-names>T</given-names></name><name><surname>Al-Masri</surname><given-names>M</given-names></name><name><surname>Watson</surname><given-names>JT</given-names></name><name><surname>Assiri</surname><given-names>A</given-names></name><name><surname>Erdman</surname><given-names>DD</given-names></name></person-group><year>2017</year><article-title>Spike gene deletion quasispecies in serum of patient with acute MERS-CoV infection</article-title><source>Journal of Medical Virology</source><volume>89</volume><fpage>542</fpage><lpage>545</lpage><pub-id pub-id-type="doi">10.1002/jmv.24652</pub-id><pub-id pub-id-type="pmid">27486688</pub-id></element-citation></ref><ref id="bib64"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lycett</surname><given-names>S</given-names></name><name><surname>Bodewes</surname><given-names>R</given-names></name><name><surname>Pohlmann</surname><given-names>A</given-names></name><name><surname>Banks</surname><given-names>J</given-names></name><name><surname>Banyai</surname><given-names>K</given-names></name><name><surname>Boni</surname><given-names>M</given-names></name><name><surname>Bouwstra</surname><given-names>R</given-names></name><name><surname>Breed</surname><given-names>A</given-names></name><name><surname>Brown</surname><given-names>I</given-names></name><name><surname>Chen</surname><given-names>H</given-names></name><collab>Global Consortium for H5N8 and Related Influenza Viruses</collab></person-group><year>2016</year><article-title>Role for migratory wild birds in the global spread of avian influenza H5N8</article-title><source>Science</source><volume>354</volume><fpage>213</fpage><lpage>217</lpage><pub-id pub-id-type="doi">10.1126/science.aaf8852</pub-id><pub-id pub-id-type="pmid">27738169</pub-id></element-citation></ref><ref id="bib65"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Makino</surname><given-names>S</given-names></name><name><surname>Keck</surname><given-names>JG</given-names></name><name><surname>Stohlman</surname><given-names>SA</given-names></name><name><surname>Lai</surname><given-names>MM</given-names></name></person-group><year>1986</year><article-title>High-frequency RNA recombination of murine coronaviruses</article-title><source>Journal of Virology</source><volume>57</volume><fpage>729</fpage><lpage>737</lpage><pub-id pub-id-type="pmid">3005623</pub-id></element-citation></ref><ref id="bib66"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Martinez</surname><given-names>VP</given-names></name><name><surname>Bellomo</surname><given-names>C</given-names></name><name><surname>San Juan</surname><given-names>J</given-names></name><name><surname>Pinna</surname><given-names>D</given-names></name><name><surname>Forlenza</surname><given-names>R</given-names></name><name><surname>Elder</surname><given-names>M</given-names></name><name><surname>Padula</surname><given-names>PJ</given-names></name></person-group><year>2005</year><article-title>Person-to-person transmission of Andes virus</article-title><source>Emerging Infectious Diseases</source><volume>11</volume><fpage>1848</fpage><lpage>1853</lpage><pub-id pub-id-type="doi">10.3201/eid1112.050501</pub-id><pub-id pub-id-type="pmid">16485469</pub-id></element-citation></ref><ref id="bib67"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Martinez-Bakker</surname><given-names>M</given-names></name><name><surname>Bakker</surname><given-names>KM</given-names></name><name><surname>King</surname><given-names>AA</given-names></name><name><surname>Rohani</surname><given-names>P</given-names></name></person-group><year>2014</year><article-title>Human birth seasonality: latitudinal gradient and interplay with childhood disease dynamics</article-title><source>Proceedings of the Royal Society B: Biological Sciences</source><volume>281</volume><elocation-id>20132438</elocation-id><pub-id pub-id-type="doi">10.1098/rspb.2013.2438</pub-id><pub-id pub-id-type="pmid">24695423</pub-id></element-citation></ref><ref id="bib68"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Memish</surname><given-names>ZA</given-names></name><name><surname>Cotten</surname><given-names>M</given-names></name><name><surname>Meyer</surname><given-names>B</given-names></name><name><surname>Watson</surname><given-names>SJ</given-names></name><name><surname>Alsahafi</surname><given-names>AJ</given-names></name><name><surname>Al Rabeeah</surname><given-names>AA</given-names></name><name><surname>Corman</surname><given-names>VM</given-names></name><name><surname>Sieberg</surname><given-names>A</given-names></name><name><surname>Makhdoom</surname><given-names>HQ</given-names></name><name><surname>Assiri</surname><given-names>A</given-names></name><name><surname>Al Masri</surname><given-names>M</given-names></name><name><surname>Aldabbagh</surname><given-names>S</given-names></name><name><surname>Bosch</surname><given-names>BJ</given-names></name><name><surname>Beer</surname><given-names>M</given-names></name><name><surname>Müller</surname><given-names>MA</given-names></name><name><surname>Kellam</surname><given-names>P</given-names></name><name><surname>Drosten</surname><given-names>C</given-names></name></person-group><year>2014</year><article-title>Human infection with MERS coronavirus after exposure to infected camels, Saudi Arabia, 2013</article-title><source>Emerging Infectious Diseases</source><volume>20</volume><elocation-id>1012</elocation-id><lpage>1015</lpage><pub-id pub-id-type="doi">10.3201/eid2006.140402</pub-id><pub-id pub-id-type="pmid">24857749</pub-id></element-citation></ref><ref id="bib69"><element-citation publication-type="preprint"><person-group person-group-type="author"><name><surname>Mueller</surname><given-names>NF</given-names></name><name><surname>Rasmussen</surname><given-names>DA</given-names></name><name><surname>Stadler</surname><given-names>T</given-names></name></person-group><year>2017</year><article-title>MASCOT: Parameter and state inference under the marginal structured coalescent approximation</article-title><source>bioRxiv</source><pub-id pub-id-type="doi">10.1101/188516</pub-id></element-citation></ref><ref id="bib70"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Müller</surname><given-names>MA</given-names></name><name><surname>Corman</surname><given-names>VM</given-names></name><name><surname>Jores</surname><given-names>J</given-names></name><name><surname>Meyer</surname><given-names>B</given-names></name><name><surname>Younan</surname><given-names>M</given-names></name><name><surname>Liljander</surname><given-names>A</given-names></name><name><surname>Bosch</surname><given-names>BJ</given-names></name><name><surname>Lattwein</surname><given-names>E</given-names></name><name><surname>Hilali</surname><given-names>M</given-names></name><name><surname>Musa</surname><given-names>BE</given-names></name><name><surname>Bornstein</surname><given-names>S</given-names></name><name><surname>Drosten</surname><given-names>C</given-names></name></person-group><year>2014</year><article-title>MERS coronavirus neutralizing antibodies in camels, Eastern Africa, 1983-1997</article-title><source>Emerging Infectious Diseases</source><volume>20</volume><fpage>2093-5</fpage><pub-id pub-id-type="doi">10.3201/eid2012.141026</pub-id><pub-id pub-id-type="pmid">25425139</pub-id></element-citation></ref><ref id="bib71"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Müller</surname><given-names>MA</given-names></name><name><surname>Meyer</surname><given-names>B</given-names></name><name><surname>Corman</surname><given-names>VM</given-names></name><name><surname>Al-Masri</surname><given-names>M</given-names></name><name><surname>Turkestani</surname><given-names>A</given-names></name><name><surname>Ritz</surname><given-names>D</given-names></name><name><surname>Sieberg</surname><given-names>A</given-names></name><name><surname>Aldabbagh</surname><given-names>S</given-names></name><name><surname>Bosch</surname><given-names>BJ</given-names></name><name><surname>Lattwein</surname><given-names>E</given-names></name><name><surname>Alhakeem</surname><given-names>RF</given-names></name><name><surname>Assiri</surname><given-names>AM</given-names></name><name><surname>Albarrak</surname><given-names>AM</given-names></name><name><surname>Al-Shangiti</surname><given-names>AM</given-names></name><name><surname>Al-Tawfiq</surname><given-names>JA</given-names></name><name><surname>Wikramaratna</surname><given-names>P</given-names></name><name><surname>Alrabeeah</surname><given-names>AA</given-names></name><name><surname>Drosten</surname><given-names>C</given-names></name><name><surname>Memish</surname><given-names>ZA</given-names></name></person-group><year>2015</year><article-title>Presence of Middle East respiratory syndrome coronavirus antibodies in Saudi Arabia: a nationwide, cross-sectional, serological study</article-title><source>The Lancet Infectious Diseases</source><volume>15</volume><fpage>559</fpage><lpage>564</lpage><pub-id pub-id-type="doi">10.1016/S1473-3099(15)70090-3</pub-id><pub-id pub-id-type="pmid">25863564</pub-id></element-citation></ref><ref id="bib72"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Notohara</surname><given-names>M</given-names></name></person-group><year>1990</year><article-title>The coalescent and the genealogical process in geographically structured population</article-title><source>Journal of Mathematical Biology</source><volume>29</volume><fpage>59</fpage><lpage>75</lpage><pub-id pub-id-type="doi">10.1007/BF00173909</pub-id><pub-id pub-id-type="pmid">2277236</pub-id></element-citation></ref><ref id="bib73"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Park</surname><given-names>D</given-names></name><name><surname>Huh</surname><given-names>HJ</given-names></name><name><surname>Kim</surname><given-names>YJ</given-names></name><name><surname>Son</surname><given-names>D-S</given-names></name><name><surname>Jeon</surname><given-names>H-J</given-names></name><name><surname>Im</surname><given-names>E-H</given-names></name><name><surname>Kim</surname><given-names>J-W</given-names></name><name><surname>Lee</surname><given-names>NY</given-names></name><name><surname>Kang</surname><given-names>E-S</given-names></name><name><surname>Kang</surname><given-names>CI</given-names></name><name><surname>Chung</surname><given-names>DR</given-names></name><name><surname>Ahn</surname><given-names>J-H</given-names></name><name><surname>Peck</surname><given-names>KR</given-names></name><name><surname>Choi</surname><given-names>SS</given-names></name><name><surname>Kim</surname><given-names>Y-J</given-names></name><name><surname>Ki</surname><given-names>C-S</given-names></name><name><surname>Park</surname><given-names>W-Y</given-names></name></person-group><year>2016a</year><article-title>Analysis of intra-patient heterogeneity uncovers the microevolution of Middle East respiratory syndrome coronavirus</article-title><source>Molecular Case Studies</source><fpage>mcs.a001214</fpage><pub-id pub-id-type="doi">10.1101/mcs.a001214</pub-id></element-citation></ref><ref id="bib74"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Park</surname><given-names>M</given-names></name><name><surname>Loverdo</surname><given-names>C</given-names></name><name><surname>Schreiber</surname><given-names>SJ</given-names></name><name><surname>Lloyd-Smith</surname><given-names>JO</given-names></name></person-group><year>2013</year><article-title>Multiple scales of selection influence the evolutionary emergence of novel pathogens</article-title><source>Philosophical Transactions of the Royal Society B: Biological Sciences</source><volume>368</volume><elocation-id>20120333</elocation-id><pub-id pub-id-type="doi">10.1098/rstb.2012.0333</pub-id><pub-id pub-id-type="pmid">23382433</pub-id></element-citation></ref><ref id="bib75"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Park</surname><given-names>WB</given-names></name><name><surname>Kwon</surname><given-names>NJ</given-names></name><name><surname>Choe</surname><given-names>PG</given-names></name><name><surname>Choi</surname><given-names>SJ</given-names></name><name><surname>Oh</surname><given-names>HS</given-names></name><name><surname>Lee</surname><given-names>SM</given-names></name><name><surname>Chong</surname><given-names>H</given-names></name><name><surname>Kim</surname><given-names>JI</given-names></name><name><surname>Song</surname><given-names>KH</given-names></name><name><surname>Bang</surname><given-names>JH</given-names></name><name><surname>Kim</surname><given-names>ES</given-names></name><name><surname>Kim</surname><given-names>HB</given-names></name><name><surname>Park</surname><given-names>SW</given-names></name><name><surname>Kim</surname><given-names>NJ</given-names></name><name><surname>Oh</surname><given-names>MD</given-names></name></person-group><year>2016b</year><article-title>Isolation of Middle East Respiratory Syndrome Coronavirus from a Patient of the 2015 Korean Outbreak</article-title><source>Journal of Korean Medical Science</source><volume>31</volume><fpage>315</fpage><lpage>335</lpage><pub-id pub-id-type="doi">10.3346/jkms.2016.31.2.315</pub-id><pub-id pub-id-type="pmid">26839489</pub-id></element-citation></ref><ref id="bib76"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Plipat</surname><given-names>T</given-names></name><name><surname>Buathong</surname><given-names>R</given-names></name><name><surname>Wacharapluesadee</surname><given-names>S</given-names></name><name><surname>Siriarayapon</surname><given-names>P</given-names></name><name><surname>Pittayawonganon</surname><given-names>C</given-names></name><name><surname>Sangsajja</surname><given-names>C</given-names></name><name><surname>Kaewpom</surname><given-names>T</given-names></name><name><surname>Petcharat</surname><given-names>S</given-names></name><name><surname>Ponpinit</surname><given-names>T</given-names></name><name><surname>Jumpasri</surname><given-names>J</given-names></name><name><surname>Joyjinda</surname><given-names>Y</given-names></name><name><surname>Rodpan</surname><given-names>A</given-names></name><name><surname>Ghai</surname><given-names>S</given-names></name><name><surname>Jittmittraphap</surname><given-names>A</given-names></name><name><surname>Khongwichit</surname><given-names>S</given-names></name><name><surname>Smith</surname><given-names>DR</given-names></name><name><surname>Corman</surname><given-names>VM</given-names></name><name><surname>Drosten</surname><given-names>C</given-names></name><name><surname>Hemachudha</surname><given-names>T</given-names></name></person-group><year>2017</year><article-title>Imported case of Middle East respiratory syndrome coronavirus (MERS-CoV) infection from Oman to Thailand, June 2015</article-title><source>Eurosurveillance</source><volume>22</volume><pub-id pub-id-type="doi">10.2807/1560-7917.ES.2017.22.33.30598</pub-id><pub-id pub-id-type="pmid">28840828</pub-id></element-citation></ref><ref id="bib77"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Quick</surname><given-names>J</given-names></name><name><surname>Ashton</surname><given-names>P</given-names></name><name><surname>Calus</surname><given-names>S</given-names></name><name><surname>Chatt</surname><given-names>C</given-names></name><name><surname>Gossain</surname><given-names>S</given-names></name><name><surname>Hawker</surname><given-names>J</given-names></name><name><surname>Nair</surname><given-names>S</given-names></name><name><surname>Neal</surname><given-names>K</given-names></name><name><surname>Nye</surname><given-names>K</given-names></name><name><surname>Peters</surname><given-names>T</given-names></name><name><surname>De Pinna</surname><given-names>E</given-names></name><name><surname>Robinson</surname><given-names>E</given-names></name><name><surname>Struthers</surname><given-names>K</given-names></name><name><surname>Webber</surname><given-names>M</given-names></name><name><surname>Catto</surname><given-names>A</given-names></name><name><surname>Dallman</surname><given-names>TJ</given-names></name><name><surname>Hawkey</surname><given-names>P</given-names></name><name><surname>Loman</surname><given-names>NJ</given-names></name></person-group><year>2015</year><article-title>Rapid draft sequencing and real-time nanopore sequencing in a hospital outbreak of Salmonella</article-title><source>Genome Biology</source><volume>16</volume><elocation-id>114</elocation-id><pub-id pub-id-type="doi">10.1186/s13059-015-0677-2</pub-id><pub-id pub-id-type="pmid">26025440</pub-id></element-citation></ref><ref id="bib78"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Raj</surname><given-names>VS</given-names></name><name><surname>Farag</surname><given-names>EA</given-names></name><name><surname>Reusken</surname><given-names>CB</given-names></name><name><surname>Lamers</surname><given-names>MM</given-names></name><name><surname>Pas</surname><given-names>SD</given-names></name><name><surname>Voermans</surname><given-names>J</given-names></name><name><surname>Smits</surname><given-names>SL</given-names></name><name><surname>Osterhaus</surname><given-names>AD</given-names></name><name><surname>Al-Mawlawi</surname><given-names>N</given-names></name><name><surname>Al-Romaihi</surname><given-names>HE</given-names></name><name><surname>AlHajri</surname><given-names>MM</given-names></name><name><surname>El-Sayed</surname><given-names>AM</given-names></name><name><surname>Mohran</surname><given-names>KA</given-names></name><name><surname>Ghobashy</surname><given-names>H</given-names></name><name><surname>Alhajri</surname><given-names>F</given-names></name><name><surname>Al-Thani</surname><given-names>M</given-names></name><name><surname>Al-Marri</surname><given-names>SA</given-names></name><name><surname>El-Maghraby</surname><given-names>MM</given-names></name><name><surname>Koopmans</surname><given-names>MP</given-names></name><name><surname>Haagmans</surname><given-names>BL</given-names></name></person-group><year>2014</year><article-title>Isolation of MERS coronavirus from a dromedary camel, Qatar, 2014</article-title><source>Emerging Infectious Diseases</source><volume>20</volume><fpage>1339</fpage><lpage>1381</lpage><pub-id pub-id-type="doi">10.3201/eid2008.140663</pub-id><pub-id pub-id-type="pmid">25075761</pub-id></element-citation></ref><ref id="bib79"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Rasmussen</surname><given-names>DA</given-names></name><name><surname>Volz</surname><given-names>EM</given-names></name><name><surname>Koelle</surname><given-names>K</given-names></name></person-group><year>2014</year><article-title>Phylodynamic inference for structured epidemiological models</article-title><source>PLoS Computational Biology</source><volume>10</volume><elocation-id>e1003570</elocation-id><pub-id pub-id-type="doi">10.1371/journal.pcbi.1003570</pub-id><pub-id pub-id-type="pmid">24743590</pub-id></element-citation></ref><ref id="bib80"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Reed</surname><given-names>KD</given-names></name><name><surname>Melski</surname><given-names>JW</given-names></name><name><surname>Graham</surname><given-names>MB</given-names></name><name><surname>Regnery</surname><given-names>RL</given-names></name><name><surname>Sotir</surname><given-names>MJ</given-names></name><name><surname>Wegner</surname><given-names>MV</given-names></name><name><surname>Kazmierczak</surname><given-names>JJ</given-names></name><name><surname>Stratman</surname><given-names>EJ</given-names></name><name><surname>Li</surname><given-names>Y</given-names></name><name><surname>Fairley</surname><given-names>JA</given-names></name><name><surname>Swain</surname><given-names>GR</given-names></name><name><surname>Olson</surname><given-names>VA</given-names></name><name><surname>Sargent</surname><given-names>EK</given-names></name><name><surname>Kehl</surname><given-names>SC</given-names></name><name><surname>Frace</surname><given-names>MA</given-names></name><name><surname>Kline</surname><given-names>R</given-names></name><name><surname>Foldy</surname><given-names>SL</given-names></name><name><surname>Davis</surname><given-names>JP</given-names></name><name><surname>Damon</surname><given-names>IK</given-names></name></person-group><year>2004</year><article-title>The detection of monkeypox in humans in the Western Hemisphere</article-title><source>New England Journal of Medicine</source><volume>350</volume><fpage>342</fpage><lpage>350</lpage><pub-id pub-id-type="doi">10.1056/NEJMoa032299</pub-id><pub-id pub-id-type="pmid">14736926</pub-id></element-citation></ref><ref id="bib81"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Reusken</surname><given-names>CB</given-names></name><name><surname>Farag</surname><given-names>EA</given-names></name><name><surname>Haagmans</surname><given-names>BL</given-names></name><name><surname>Mohran</surname><given-names>KA</given-names></name><name><surname>Godeke</surname><given-names>GJ</given-names></name><name><surname>Raj</surname><given-names>S</given-names></name><name><surname>Alhajri</surname><given-names>F</given-names></name><name><surname>Al-Marri</surname><given-names>SA</given-names></name><name><surname>Al-Romaihi</surname><given-names>HE</given-names></name><name><surname>Al-Thani</surname><given-names>M</given-names></name><name><surname>Bosch</surname><given-names>BJ</given-names></name><name><surname>van der Eijk</surname><given-names>AA</given-names></name><name><surname>El-Sayed</surname><given-names>AM</given-names></name><name><surname>Ibrahim</surname><given-names>AK</given-names></name><name><surname>Al-Molawi</surname><given-names>N</given-names></name><name><surname>Müller</surname><given-names>MA</given-names></name><name><surname>Pasha</surname><given-names>SK</given-names></name><name><surname>Drosten</surname><given-names>C</given-names></name><name><surname>AlHajri</surname><given-names>MM</given-names></name><name><surname>Koopmans</surname><given-names>MP</given-names></name></person-group><year>2015</year><article-title>Occupational exposure to dromedaries and risk for MERS-CoV infection, Qatar, 2013-2014</article-title><source>Emerging Infectious Diseases</source><volume>21</volume><fpage>1422</fpage><lpage>1425</lpage><pub-id pub-id-type="doi">10.3201/eid2108.150481</pub-id><pub-id pub-id-type="pmid">26196891</pub-id></element-citation></ref><ref id="bib82"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Reusken</surname><given-names>CB</given-names></name><name><surname>Haagmans</surname><given-names>BL</given-names></name><name><surname>Müller</surname><given-names>MA</given-names></name><name><surname>Gutierrez</surname><given-names>C</given-names></name><name><surname>Godeke</surname><given-names>GJ</given-names></name><name><surname>Meyer</surname><given-names>B</given-names></name><name><surname>Muth</surname><given-names>D</given-names></name><name><surname>Raj</surname><given-names>VS</given-names></name><name><surname>Smits-De Vries</surname><given-names>L</given-names></name><name><surname>Corman</surname><given-names>VM</given-names></name><name><surname>Drexler</surname><given-names>JF</given-names></name><name><surname>Smits</surname><given-names>SL</given-names></name><name><surname>El Tahir</surname><given-names>YE</given-names></name><name><surname>De Sousa</surname><given-names>R</given-names></name><name><surname>van Beek</surname><given-names>J</given-names></name><name><surname>Nowotny</surname><given-names>N</given-names></name><name><surname>van Maanen</surname><given-names>K</given-names></name><name><surname>Hidalgo-Hermoso</surname><given-names>E</given-names></name><name><surname>Bosch</surname><given-names>BJ</given-names></name><name><surname>Rottier</surname><given-names>P</given-names></name><name><surname>Osterhaus</surname><given-names>A</given-names></name><name><surname>Gortázar-Schmidt</surname><given-names>C</given-names></name><name><surname>Drosten</surname><given-names>C</given-names></name><name><surname>Koopmans</surname><given-names>MP</given-names></name></person-group><year>2013</year><article-title>Middle East respiratory syndrome coronavirus neutralising serum antibodies in dromedary camels: a comparative serological study</article-title><source>The Lancet Infectious Diseases</source><volume>13</volume><fpage>859</fpage><lpage>866</lpage><pub-id pub-id-type="doi">10.1016/S1473-3099(13)70164-6</pub-id><pub-id pub-id-type="pmid">23933067</pub-id></element-citation></ref><ref id="bib83"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Reusken</surname><given-names>CB</given-names></name><name><surname>Messadi</surname><given-names>L</given-names></name><name><surname>Feyisa</surname><given-names>A</given-names></name><name><surname>Ularamu</surname><given-names>H</given-names></name><name><surname>Godeke</surname><given-names>GJ</given-names></name><name><surname>Danmarwa</surname><given-names>A</given-names></name><name><surname>Dawo</surname><given-names>F</given-names></name><name><surname>Jemli</surname><given-names>M</given-names></name><name><surname>Melaku</surname><given-names>S</given-names></name><name><surname>Shamaki</surname><given-names>D</given-names></name><name><surname>Woma</surname><given-names>Y</given-names></name><name><surname>Wungak</surname><given-names>Y</given-names></name><name><surname>Gebremedhin</surname><given-names>EZ</given-names></name><name><surname>Zutt</surname><given-names>I</given-names></name><name><surname>Bosch</surname><given-names>BJ</given-names></name><name><surname>Haagmans</surname><given-names>BL</given-names></name><name><surname>Koopmans</surname><given-names>MP</given-names></name></person-group><year>2014</year><article-title>Geographic distribution of MERS coronavirus among dromedary camels, Africa</article-title><source>Emerging Infectious Diseases</source><volume>20</volume><fpage>1370</fpage><lpage>1374</lpage><pub-id pub-id-type="doi">10.3201/eid2008.140590</pub-id><pub-id pub-id-type="pmid">25062254</pub-id></element-citation></ref><ref id="bib84"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Sabir</surname><given-names>JS</given-names></name><name><surname>Lam</surname><given-names>TT</given-names></name><name><surname>Ahmed</surname><given-names>MM</given-names></name><name><surname>Li</surname><given-names>L</given-names></name><name><surname>Shen</surname><given-names>Y</given-names></name><name><surname>Abo-Aba</surname><given-names>SE</given-names></name><name><surname>Qureshi</surname><given-names>MI</given-names></name><name><surname>Abu-Zeid</surname><given-names>M</given-names></name><name><surname>Zhang</surname><given-names>Y</given-names></name><name><surname>Khiyami</surname><given-names>MA</given-names></name><name><surname>Alharbi</surname><given-names>NS</given-names></name><name><surname>Hajrah</surname><given-names>NH</given-names></name><name><surname>Sabir</surname><given-names>MJ</given-names></name><name><surname>Mutwakil</surname><given-names>MH</given-names></name><name><surname>Kabli</surname><given-names>SA</given-names></name><name><surname>Alsulaimany</surname><given-names>FA</given-names></name><name><surname>Obaid</surname><given-names>AY</given-names></name><name><surname>Zhou</surname><given-names>B</given-names></name><name><surname>Smith</surname><given-names>DK</given-names></name><name><surname>Holmes</surname><given-names>EC</given-names></name><name><surname>Zhu</surname><given-names>H</given-names></name><name><surname>Guan</surname><given-names>Y</given-names></name></person-group><year>2016</year><article-title>Co-circulation of three camel coronavirus species and recombination of MERS-CoVs in Saudi Arabia</article-title><source>Science</source><volume>351</volume><fpage>81</fpage><lpage>84</lpage><pub-id pub-id-type="doi">10.1126/science.aac8608</pub-id><pub-id pub-id-type="pmid">26678874</pub-id></element-citation></ref><ref id="bib85"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Seong</surname><given-names>MW</given-names></name><name><surname>Kim</surname><given-names>SY</given-names></name><name><surname>Corman</surname><given-names>VM</given-names></name><name><surname>Kim</surname><given-names>TS</given-names></name><name><surname>Cho</surname><given-names>SI</given-names></name><name><surname>Kim</surname><given-names>MJ</given-names></name><name><surname>Lee</surname><given-names>SJ</given-names></name><name><surname>Lee</surname><given-names>JS</given-names></name><name><surname>Seo</surname><given-names>SH</given-names></name><name><surname>Ahn</surname><given-names>JS</given-names></name><name><surname>Yu</surname><given-names>BS</given-names></name><name><surname>Park</surname><given-names>N</given-names></name><name><surname>Oh</surname><given-names>MD</given-names></name><name><surname>Park</surname><given-names>WB</given-names></name><name><surname>Lee</surname><given-names>JY</given-names></name><name><surname>Kim</surname><given-names>G</given-names></name><name><surname>Joh</surname><given-names>JS</given-names></name><name><surname>Jeong</surname><given-names>I</given-names></name><name><surname>Kim</surname><given-names>EC</given-names></name><name><surname>Drosten</surname><given-names>C</given-names></name><name><surname>Park</surname><given-names>SS</given-names></name></person-group><year>2016</year><article-title>Microevolution of Outbreak-Associated Middle East Respiratory Syndrome Coronavirus, South Korea, 2015</article-title><source>Emerging Infectious Diseases</source><volume>22</volume><fpage>327</fpage><lpage>357</lpage><pub-id pub-id-type="doi">10.3201/eid2202.151700</pub-id><pub-id pub-id-type="pmid">26814649</pub-id></element-citation></ref><ref id="bib86"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Smith</surname><given-names>GJ</given-names></name><name><surname>Bahl</surname><given-names>J</given-names></name><name><surname>Vijaykrishna</surname><given-names>D</given-names></name><name><surname>Zhang</surname><given-names>J</given-names></name><name><surname>Poon</surname><given-names>LL</given-names></name><name><surname>Chen</surname><given-names>H</given-names></name><name><surname>Webster</surname><given-names>RG</given-names></name><name><surname>Peiris</surname><given-names>JS</given-names></name><name><surname>Guan</surname><given-names>Y</given-names></name></person-group><year>2009</year><article-title>Dating the emergence of pandemic influenza viruses</article-title><source>PNAS</source><volume>106</volume><fpage>11709</fpage><lpage>11712</lpage><pub-id pub-id-type="doi">10.1073/pnas.0904991106</pub-id><pub-id pub-id-type="pmid">19597152</pub-id></element-citation></ref><ref id="bib87"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Turner</surname><given-names>TL</given-names></name><name><surname>Hahn</surname><given-names>MW</given-names></name><name><surname>Nuzhdin</surname><given-names>SV</given-names></name></person-group><year>2005</year><article-title>Genomic islands of speciation in Anopheles gambiae</article-title><source>PLoS Biology</source><volume>3</volume><elocation-id>e285</elocation-id><pub-id pub-id-type="doi">10.1371/journal.pbio.0030285</pub-id><pub-id pub-id-type="pmid">16076241</pub-id></element-citation></ref><ref id="bib88"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>van Boheemen</surname><given-names>S</given-names></name><name><surname>de Graaf</surname><given-names>M</given-names></name><name><surname>Lauber</surname><given-names>C</given-names></name><name><surname>Bestebroer</surname><given-names>TM</given-names></name><name><surname>Raj</surname><given-names>VS</given-names></name><name><surname>Zaki</surname><given-names>AM</given-names></name><name><surname>Osterhaus</surname><given-names>AD</given-names></name><name><surname>Haagmans</surname><given-names>BL</given-names></name><name><surname>Gorbalenya</surname><given-names>AE</given-names></name><name><surname>Snijder</surname><given-names>EJ</given-names></name><name><surname>Fouchier</surname><given-names>RA</given-names></name></person-group><year>2012</year><article-title>Genomic characterization of a newly discovered coronavirus associated with acute respiratory distress syndrome in humans</article-title><source>mBio</source><volume>3</volume><fpage>e00473</fpage><lpage>12</lpage><pub-id pub-id-type="doi">10.1128/mBio.00473-12</pub-id><pub-id pub-id-type="pmid">23170002</pub-id></element-citation></ref><ref id="bib89"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Vaughan</surname><given-names>TG</given-names></name><name><surname>Kühnert</surname><given-names>D</given-names></name><name><surname>Popinga</surname><given-names>A</given-names></name><name><surname>Welch</surname><given-names>D</given-names></name><name><surname>Drummond</surname><given-names>AJ</given-names></name></person-group><year>2014</year><article-title>Efficient Bayesian inference under the structured coalescent</article-title><source>Bioinformatics</source><volume>30</volume><fpage>2272</fpage><lpage>2279</lpage><pub-id pub-id-type="doi">10.1093/bioinformatics/btu201</pub-id><pub-id pub-id-type="pmid">24753484</pub-id></element-citation></ref><ref id="bib90"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Volz</surname><given-names>EM</given-names></name><name><surname>Koelle</surname><given-names>K</given-names></name><name><surname>Bedford</surname><given-names>T</given-names></name></person-group><year>2013</year><article-title>Viral phylodynamics</article-title><source>PLoS Computational Biology</source><volume>9</volume><elocation-id>e1002947</elocation-id><pub-id pub-id-type="doi">10.1371/journal.pcbi.1002947</pub-id><pub-id pub-id-type="pmid">23555203</pub-id></element-citation></ref><ref id="bib91"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Volz</surname><given-names>EM</given-names></name></person-group><year>2012</year><article-title>Complex population dynamics and the coalescent under neutrality</article-title><source>Genetics</source><volume>190</volume><fpage>187</fpage><lpage>201</lpage><pub-id pub-id-type="doi">10.1534/genetics.111.134627</pub-id><pub-id pub-id-type="pmid">22042576</pub-id></element-citation></ref><ref id="bib92"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Wernery</surname><given-names>U</given-names></name><name><surname>Corman</surname><given-names>VM</given-names></name><name><surname>Wong</surname><given-names>EY</given-names></name><name><surname>Tsang</surname><given-names>AK</given-names></name><name><surname>Muth</surname><given-names>D</given-names></name><name><surname>Lau</surname><given-names>SK</given-names></name><name><surname>Khazanehdari</surname><given-names>K</given-names></name><name><surname>Zirkel</surname><given-names>F</given-names></name><name><surname>Ali</surname><given-names>M</given-names></name><name><surname>Nagy</surname><given-names>P</given-names></name><name><surname>Juhasz</surname><given-names>J</given-names></name><name><surname>Wernery</surname><given-names>R</given-names></name><name><surname>Joseph</surname><given-names>S</given-names></name><name><surname>Syriac</surname><given-names>G</given-names></name><name><surname>Elizabeth</surname><given-names>SK</given-names></name><name><surname>Patteril</surname><given-names>NA</given-names></name><name><surname>Woo</surname><given-names>PC</given-names></name><name><surname>Drosten</surname><given-names>C</given-names></name></person-group><year>2015</year><article-title>Acute Middle East respiratory syndrome coronavirus infection in livestock Dromedaries, Dubai, 2014</article-title><source>Emerging Infectious Diseases</source><volume>21</volume><elocation-id>1019</elocation-id><lpage>1022</lpage><pub-id pub-id-type="doi">10.3201/eid2106.150038</pub-id><pub-id pub-id-type="pmid">25989145</pub-id></element-citation></ref><ref id="bib93"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Wernery</surname><given-names>U</given-names></name></person-group><year>2001</year><article-title>Camelid immunoglobulins and their importance for the new-born--a review</article-title><source>Journal of Veterinary Medicine Series B</source><volume>48</volume><fpage>561</fpage><lpage>568</lpage><pub-id pub-id-type="doi">10.1046/j.1439-0450.2001.00478.x</pub-id><pub-id pub-id-type="pmid">11708675</pub-id></element-citation></ref><ref id="bib94"><element-citation publication-type="journal"><person-group person-group-type="author"><collab>WHO MERS-Cov Research Group</collab></person-group><year>2013</year><article-title>State of knowledge and data gaps of Middle East respiratory syndromecoronavirus (MERS-CoV) in humans</article-title><source>PLoS Currents</source><volume>5</volume><pub-id pub-id-type="doi">10.1371/currents.outbreaks.0bf719e352e7478f8ad85fa30127ddb8</pub-id></element-citation></ref><ref id="bib95"><element-citation publication-type="web"><person-group person-group-type="author"><collab>World Health Organization</collab></person-group><year>2016</year><article-title>Disease outbreak news</article-title><ext-link ext-link-type="uri" xlink:href="http://www.who.int/csr/don/19-december-2016-2-mers-saudi-arabia/en/">http://www.who.int/csr/don/19-december-2016-2-mers-saudi-arabia/en/</ext-link><date-in-citation iso-8601-date="2017-08">August 2017</date-in-citation></element-citation></ref><ref id="bib96"><element-citation publication-type="web"><person-group person-group-type="author"><collab>World Health Organization</collab></person-group><year>2017</year><article-title>WHO MERS-CoV global summary and assessment of risk</article-title><ext-link ext-link-type="uri" xlink:href="http://www.who.int/emergencies/mers-cov/risk-assessment-july-2017.pdf">http://www.who.int/emergencies/mers-cov/risk-assessment-july-2017.pdf</ext-link><date-in-citation iso-8601-date="2017-08">August 2017</date-in-citation></element-citation></ref><ref id="bib97"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Xie</surname><given-names>Q</given-names></name><name><surname>Cao</surname><given-names>Y</given-names></name><name><surname>Su</surname><given-names>J</given-names></name><name><surname>Wu</surname><given-names>X</given-names></name><name><surname>Wan</surname><given-names>C</given-names></name><name><surname>Ke</surname><given-names>C</given-names></name><name><surname>Zhao</surname><given-names>W</given-names></name><name><surname>Zhang</surname><given-names>B</given-names></name></person-group><year>2015</year><article-title>Genomic sequencing and analysis of the first imported Middle East Respiratory Syndrome Coronavirus (MERS CoV) in China</article-title><source>Science China Life Sciences</source><volume>58</volume><fpage>818</fpage><lpage>820</lpage><pub-id pub-id-type="doi">10.1007/s11427-015-4903-7</pub-id><pub-id pub-id-type="pmid">26199186</pub-id></element-citation></ref><ref id="bib98"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Yang</surname><given-names>Z</given-names></name></person-group><year>1994</year><article-title>Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods</article-title><source>Journal of Molecular Evolution</source><volume>39</volume><fpage>306</fpage><lpage>314</lpage><pub-id pub-id-type="doi">10.1007/BF00160154</pub-id><pub-id pub-id-type="pmid">7932792</pub-id></element-citation></ref><ref id="bib99"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Zaki</surname><given-names>AM</given-names></name><name><surname>van Boheemen</surname><given-names>S</given-names></name><name><surname>Bestebroer</surname><given-names>TM</given-names></name><name><surname>Osterhaus</surname><given-names>AD</given-names></name><name><surname>Fouchier</surname><given-names>RA</given-names></name></person-group><year>2012</year><article-title>Isolation of a novel coronavirus from a man with pneumonia in Saudi Arabia</article-title><source>New England Journal of Medicine</source><volume>367</volume><fpage>1814</fpage><lpage>1820</lpage><pub-id pub-id-type="doi">10.1056/NEJMoa1211721</pub-id><pub-id pub-id-type="pmid">23075143</pub-id></element-citation></ref><ref id="bib100"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Zhang</surname><given-names>Z</given-names></name><name><surname>Shen</surname><given-names>L</given-names></name><name><surname>Gu</surname><given-names>X</given-names></name></person-group><year>2016</year><article-title>Evolutionary dynamics of MERS-CoV: potential recombination, positive selection and transmission</article-title><source>Scientific Reports</source><volume>6</volume><elocation-id>25049</elocation-id><pub-id pub-id-type="doi">10.1038/srep25049</pub-id><pub-id pub-id-type="pmid">27142087</pub-id></element-citation></ref></ref-list></back><sub-article id="SA1" article-type="decision-letter"><front-stub><article-id pub-id-type="doi">10.7554/eLife.31257.037</article-id><title-group><article-title>Decision letter</article-title></title-group><contrib-group><contrib contrib-type="editor"><name><surname>Ferguson</surname><given-names>Neil M</given-names></name><role>Reviewing Editor</role><aff id="aff5"><institution>Imperial College London</institution><country>United Kingdom</country></aff></contrib></contrib-group></front-stub><body><boxed-text position="float" orientation="portrait"><p>In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.</p></boxed-text><p>Thank you for submitting your article "MERS-CoV spillover at the camel-human interface" for consideration by <italic>eLife</italic>. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Prabhat Jha as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Erik Volz (Reviewer #1); Christophe Fraser (Reviewer #3).</p><p>The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.</p><p>Summary:</p><p>In this paper, Dudas et al. perform a coalescent analysis of 274 MERS-Cov viruses. They conclude that 1) MERS is sustained in camels (R0>1) and not in humans (R0<1), and that most if not all cross species transmissions have been camel to human. 2) Cross species events are seasonal, but R0 in humans isn't. 3) The relatively low levels of genetic diversity in camel viruses can be explained by camel demography.</p><p>Essential revisions:</p><p>1) The population genetic model (the particular form of structured coalescent) is highly idealised and this may influence the quantitative conclusions, although we suspect the conclusions are quite robust qualitatively. This model specifically estimates the rate of a lineage moving between demes going backwards in time; the numbers cited for the camel->human rate is really the rate that a lineage in humans goes to a camel going down the tree. The relationship between these migration rates and the epidemiologically meaningful transmission rate is complex and depends among other things on the ratio of population sizes in both demes. Per-capita transmission rates could be estimated using an epidemiologically structured coalescent model (see e.g. papers by Volz and Rasmussen), which would ideally be stochastic due to bursty dynamics in humans. But this would be a large undertaking and so we suggest that for now the distinction is clarified. Overall, a little more discussion of the complexity and pitfalls when relating idealised population genetic models (like the island model used here) to a noisy nonlinear epidemic like this one might be merited.</p><p>2) 'Our analyses recover these results despite sequence data heavily skewed towards non-uniformly sampled human cases and are robust to choice of prior.' This is a quite nice result and raises the question if skewed sampling would bias estimates if using a substitution model approach ('discrete trait analysis', DTA). It would strengthen the paper to include a comparison of the structured coalescent estimates to another method for ancestral states; the most popular approach in beast has been substitution models (DTA). These may give divergent results because of skewed sampling. It would be rather easy for the authors to run a DTA and if biased, this would serve as a good cautionary example when sampling is highly skewed towards one deme.</p><p>3) A comparison to ML tree reconstruction could potentially be illuminating. We think you could be clearer about what drives the results in your paper. It is unusual for a phylogenetic ancestral reconstruction, that the results seem to be determined as much by the coalescent assumptions as by the tree topology. The two-patch model had a much higher coalescent rate in the human deme than in the camel deme – so long branches are only really possible in the camel deme. This may be why for example, staring at the top clade of Figure 1, one can see camel ancestry to a whole bunch of human sequences that are not topologically separated by camel sequences. If this is correct, these results may not necessarily be wrong, but it made us slightly uncomfortable that the results are driven by the coalescent model, not the tree topology. Please elaborate, either correcting us, or explaining better. A simple test of this hypothesis would be that an ML ancestral reconstruction on the ML tree would not give the same clusters. I don't think that would make the ML result correct, but it might be an enlightening comparison. Or you may prefer another way to address this.</p><p>4) Easily addressed, but important. The paper already sounds a strong voice of concern in the final paragraph, but we think this could be even stronger. Antia et al. Nature 2003 first showed, using a simple branching process, that for most genetic landscapes, the probability of a pathogen evolving to state with R0>1 increases dramatically as a function of the wild-type R0. So R0~0.8 is much worse than R0~0.3. More sophisticated models have been done since, especially by Llyod-smith's group, but the basic result is sound. In the light of this theoretical work, your findings are not at all reassuring.</p><p>5) More generally, the model choices need better explaining. Why delve into a structured coalescent in BEAST2 for the ancestral reconstruction, but go back to the Skygrid in BEAST1 for computations of Ne? We assume this is a pragmatic choice, and for the latter you carefully reduced the human clusters to reduce bias, but we think the rationale for your choices need laying out more clearly. Even if pragmatic rather than principled, (e.g. there are no structure coalescent options in BEAST1), we think it still needs to be stated why you made the choices you did. Especially since there are other recently-developed BEAST2 packages that could be used to fit the same structured coalescent model: BASTA and MASCOT, as well as the very flexible PhyDyn package (which might offer improvements in computation time).</p></body></sub-article><sub-article id="SA2" article-type="reply"><front-stub><article-id pub-id-type="doi">10.7554/eLife.31257.038</article-id><title-group><article-title>Author response</article-title></title-group></front-stub><body><disp-quote content-type="editor-comment"><p>Essential revisions:</p><p>1) The population genetic model (the particular form of structured coalescent) is highly idealised and this may influence the quantitative conclusions, although we suspect the conclusions are quite robust qualitatively. This model specifically estimates the rate of a lineage moving between demes going backwards in time; the numbers cited for the camel->human rate is really the rate that a lineage in humans goes to a camel going down the tree. The relationship between these migration rates and the epidemiologically meaningful transmission rate is complex and depends among other things on the ratio of population sizes in both demes. Per-capita transmission rates could be estimated using an epidemiologically structured coalescent model (see e.g. papers by Volz and Rasmussen), which would ideally be stochastic due to bursty dynamics in humans. But this would be a large undertaking and so we suggest that for now the distinction is clarified. Overall, a little more discussion of the complexity and pitfalls when relating idealised population genetic models (like the island model used here) to a noisy nonlinear epidemic like this one might be merited.</p></disp-quote><p>Yes, we agree that the structured coalescent approach is idealised and does not reflect a meaningful rate of zoonotic transfer of lineages, which is the reason we restricted any mention of rates to supplementary figures and do not attach numbers whenever rates are mentioned, but still report the number of introductions observed in the sequence data. We have altered Figure 1—figure supplement 2 in the reviewed manuscript to reflect that the rates shown are backwards in time. We have added the following sentences to the Discussion to highlight the fact that the coalescent model employed is not ideal:</p><p>“Although we recover migration rates from our model (Figure 1—figure supplement 2), these only pertain to sequences and in no way reflect the epidemiologically relevant per capita rates of zoonotic spillover events. […] Outside of coalescent-based models there are population structure models that explicitly relate epidemiological parameters to the branching process observed in sequence data (Kuhnert et al., 2016), but often rely on specifying numerous informative priors and can suffer from MCMC convergence issues.”</p><disp-quote content-type="editor-comment"><p>2) 'Our analyses recover these results despite sequence data heavily skewed towards non-uniformly sampled human cases and are robust to choice of prior.' This is a quite nice result and raises the question if skewed sampling would bias estimates if using a substitution model approach ('discrete trait analysis', DTA). It would strengthen the paper to include a comparison of the structured coalescent estimates to another method for ancestral states; the most popular approach in beast has been substitution models (DTA). These may give divergent results because of skewed sampling. It would be rather easy for the authors to run a DTA and if biased, this would serve as a good cautionary example when sampling is highly skewed towards one deme.</p></disp-quote><p>An excellent suggestion, thank you. We have run this analysis and include the results as a new figure supplement (Figure 1—figure supplement 3). As expected, the skewed sampling results in a reconstruction of ancestral states that puts humans as the source of most MERS-CoV lineages in camels. We have added the appropriate description of methods as well as the following paragraph in Results:</p><p>“Our findings suggest that instances of human infection with MERS-CoV are more common than currently thought, with exceedingly short transmission chains mostly limited to primary cases that might be mild and ultimately not detected by surveillance or sequencing. […] We suspect that this particular discrete trait analysis reconstruction is false due to biased data, i.e. having nearly twice as many MERS-CoV sequences from humans (n = 174) than from camels (n = 100) and the inability of the model to account for and quantify vastly different rates of coalescence in the phylogenetic vicinity of both types of sequences.”</p><disp-quote content-type="editor-comment"><p>3) A comparison to ML tree reconstruction could potentially be illuminating. We think you could be clearer about what drives the results in your paper. It is unusual for a phylogenetic ancestral reconstruction, that the results seem to be determined as much by the coalescent assumptions as by the tree topology. The two-patch model had a much higher coalescent rate in the human deme than in the camel deme – so long branches are only really possible in the camel deme. This may be why for example, staring at the top clade of Figure 1, one can see camel ancestry to a whole bunch of human sequences that are not topologically separated by camel sequences. If this is correct, these results may not necessarily be wrong, but it made us slightly uncomfortable that the results are driven by the coalescent model, not the tree topology. Please elaborate, either correcting us, or explaining better. A simple test of this hypothesis would be that an ML ancestral reconstruction on the ML tree would not give the same clusters. I don't think that would make the ML result correct, but it might be an enlightening comparison. Or you may prefer another way to address this.</p></disp-quote><p>A very good point. We share the suspicion that the results are largely driven by contrasts in effective population sizes between demes. In addition to the requested maximum likelihood phylogeny (now Figure 1—figure supplement 5) we also ran a structured coalescent analysis where deme sizes are enforced to be the same (now Figure 1—figure supplement 4). This model fails in a similar way to a DTA reconstruction shown in the Figure 1—figure supplement 3. We now explain how the structured coalescent arrives at the tree shown in Figure 1 in the Discussion:</p><p>“When allowed different deme-specific population sizes, the structured coalescent model succeeds because a large proportion of human sequences fall into tightly connected clusters, which informs a low estimate for the population size of the human deme. This in turn informs the inferred state of long ancestral branches in the phylogeny, i.e. because these long branches are not immediately coalescing, they are most likely in camels.”</p><disp-quote content-type="editor-comment"><p>4) Easily addressed, but important. The paper already sounds a strong voice of concern in the final paragraph, but we think this could be even stronger. Antia et al. Nature 2003 first showed, using a simple branching process, that for most genetic landscapes, the probability of a pathogen evolving to state with R0>1 increases dramatically as a function of the wild-type R0. So R0~0.8 is much worse than R0~0.3. More sophisticated models have been done since, especially by Llyod-smith's group, but the basic result is sound. In the light of this theoretical work, your findings are not at all reassuring.</p></disp-quote><p>We agree that this is an important point, but also feel that it is difficult to formulate warnings about pandemic potential without overstating the case. We also believe that adaptive landscapes play a considerable role in emerging pandemics. We added an additional sentence to the Discussion and refer to the Antia et al. study:</p><p>“Previous modeling studies (Antia et al., 2003; Park et al., 2013) suggest a positive relationship between initial R0 in the human host and probability of evolutionary emergence of a novel strain which passes the supercritical threshold of R0 > 1.0. […] In light of these difficulties, we encourage continued genomic surveillance of MERS-CoV in the camel reservoir and from sporadic human cases to rapidly identify a supercritical variant, if one does emerge.</p><disp-quote content-type="editor-comment"><p>5) More generally, the model choices need better explaining. Why delve into a structured coalescent in BEAST2 for the ancestral reconstruction, but go back to the Skygrid in BEAST1 for computations of Ne? We assume this is a pragmatic choice, and for the latter you carefully reduced the human clusters to reduce bias, but we think the rationale for your choices need laying out more clearly. Even if pragmatic rather than principled, (e.g. there are no structure coalescent options in BEAST1), we think it still needs to be stated why you made the choices you did. Especially since there are other recently-developed BEAST2 packages that could be used to fit the same structured coalescent model: BASTA and MASCOT, as well as the very flexible PhyDyn package (which might offer improvements in computation time).</p></disp-quote><p>In hindsight we see how our choices may have seemed arbitrary. Indeed all cases of using BEAST 1 vs. BEAST 2 came down to what models were implemented in which package. We have clarified our choices throughout the manuscript.</p></body></sub-article></pmc></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Sante/explor/MersV1/Data/Pmc/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 001228 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Pmc/Corpus/biblio.hfd -nk 001228 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Sante
|area= MersV1
|flux= Pmc
|étape= Corpus
|type= RBID
|clé= PMC:5777824
|texte= MERS-CoV spillover at the camel-human interface
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Pmc/Corpus/RBID.i -Sk "pubmed:29336306" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Pmc/Corpus/biblio.hfd \
| NlmPubMed2Wicri -a MersV1
| This area was generated with Dilib version V0.6.33. |  |