Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility
Identifieur interne : 000066 ( PascalFrancis/Curation ); précédent : 000065; suivant : 000067Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility
Auteurs : Simon Cauchemez [Royaume-Uni] ; Christophe Fraser [Royaume-Uni] ; Maria D. Van Kerkhove [Royaume-Uni] ; Christl A. Donnelly [Royaume-Uni] ; Steven Riley [Royaume-Uni] ; Andrew Rambaut [Royaume-Uni] ; Vincent Enouf [France] ; Sylvie Van Der Werf [France] ; Neil M. Ferguson [Royaume-Uni]Source :
- Lancet. Infectious diseases : (print) [ 1473-3099 ] ; 2014.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Analyse quantitative.
English descriptors
- KwdEn :
Abstract
Background The novel Middle East respiratory syndrome coronavirus (MERS-CoV) had, as of Aug 8, 2013, caused 111 virologically confirmed or probable human cases of infection worldwide. We analysed epidemiological and genetic data to assess the extent of human infection, the performance of case detection, and the transmission potential of MERS-CoV with and without control measures. Methods We assembled a comprehensive database of all confirmed and probable cases from public sources and estimated the incubation period and generation time from case cluster data. Using data of numbers of visitors to the Middle East and their duration of stay, we estimated the number of symptomatic cases in the Middle East. We did independent analyses, looking at the growth in incident clusters, the growth in viral population, the reproduction number of cluster index cases, and cluster sizes to characterise the dynamical properties of the epidemic and the transmission scenario. Findings The estimated number of symptomatic cases up to Aug 8, 2013, is 940 (95% CI 290-2200), indicating that at least 62% of human symptomatic cases have not been detected. We find that the case-fatality ratio of primary cases detected via routine surveillance (74%; 95% CI 49-91) is biased upwards because of detection bias; the case-fatality ratio of secondary cases was 20% (7-42). Detection of milder cases (or clinical management) seemed to have improved in recent months. Analysis of human clusters indicated that chains of transmission were not self-sustaining when infection control was implemented, but that Rin the absence of controls was in the range 0?8-1?3. Three independent data sources provide evidence that R cannot be much above 1, with an upper bound of 1?2-1?5. Interpretation By showing that a slowly growing epidemic is underway either in human beings or in an animal reservoir, quantification of uncertainty in transmissibility estimates, and provision of the first estimates of the scale of the epidemic and extent of case detection biases, we provide valuable information for more informed risk assessment. Funding Medical Research Council, Bill & Melinda Gates Foundation, EU FP7, and National Institute of General Medical Sciences.
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Ferguson</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London</s1><s2>London</s2><s3>GBR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ><sZ>5 aut.</sZ><sZ>9 aut.</sZ></inist:fA14><country>Royaume-Uni</country></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">14-0043018</idno><date when="2014">2014</date><idno type="stanalyst">PASCAL 14-0043018 INIST</idno><idno type="RBID">Pascal:14-0043018</idno><idno type="wicri:Area/PascalFrancis/Corpus">000028</idno><idno type="wicri:Area/PascalFrancis/Curation">000066</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility</title><author><name sortKey="Cauchemez, Simon" sort="Cauchemez, Simon" uniqKey="Cauchemez S" first="Simon" last="Cauchemez">Simon Cauchemez</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London</s1><s2>London</s2><s3>GBR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ><sZ>5 aut.</sZ><sZ>9 aut.</sZ></inist:fA14><country>Royaume-Uni</country></affiliation></author><author><name sortKey="Fraser, Christophe" sort="Fraser, Christophe" uniqKey="Fraser C" first="Christophe" last="Fraser">Christophe Fraser</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London</s1><s2>London</s2><s3>GBR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ><sZ>5 aut.</sZ><sZ>9 aut.</sZ></inist:fA14><country>Royaume-Uni</country></affiliation></author><author><name sortKey="Van Kerkhove, Maria D" sort="Van Kerkhove, Maria D" uniqKey="Van Kerkhove M" first="Maria D." last="Van Kerkhove">Maria D. Van Kerkhove</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London</s1><s2>London</s2><s3>GBR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ><sZ>5 aut.</sZ><sZ>9 aut.</sZ></inist:fA14><country>Royaume-Uni</country></affiliation></author><author><name sortKey="Donnelly, Christl A" sort="Donnelly, Christl A" uniqKey="Donnelly C" first="Christl A." last="Donnelly">Christl A. Donnelly</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London</s1><s2>London</s2><s3>GBR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ><sZ>5 aut.</sZ><sZ>9 aut.</sZ></inist:fA14><country>Royaume-Uni</country></affiliation></author><author><name sortKey="Riley, Steven" sort="Riley, Steven" uniqKey="Riley S" first="Steven" last="Riley">Steven Riley</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London</s1><s2>London</s2><s3>GBR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ><sZ>5 aut.</sZ><sZ>9 aut.</sZ></inist:fA14><country>Royaume-Uni</country></affiliation></author><author><name sortKey="Rambaut, Andrew" sort="Rambaut, Andrew" uniqKey="Rambaut A" first="Andrew" last="Rambaut">Andrew Rambaut</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh</s1><s2>Edinburgh</s2><s3>GBR</s3><sZ>6 aut.</sZ></inist:fA14><country>Royaume-Uni</country></affiliation></author><author><name sortKey="Enouf, Vincent" sort="Enouf, Vincent" uniqKey="Enouf V" first="Vincent" last="Enouf">Vincent Enouf</name><affiliation wicri:level="1"><inist:fA14 i1="03"><s1>Institut Pasteur, Unit of Molecular Genetics of RNA Viruses, UMR3569 CNRS, Universite Paris Diderot Sorbonne Paris Cité</s1><s2>Paris</s2><s3>FRA</s3><sZ>7 aut.</sZ><sZ>8 aut.</sZ></inist:fA14><country>France</country></affiliation></author><author><name sortKey="Van Der Werf, Sylvie" sort="Van Der Werf, Sylvie" uniqKey="Van Der Werf S" first="Sylvie" last="Van Der Werf">Sylvie Van Der Werf</name><affiliation wicri:level="1"><inist:fA14 i1="03"><s1>Institut Pasteur, Unit of Molecular Genetics of RNA Viruses, UMR3569 CNRS, Universite Paris Diderot Sorbonne Paris Cité</s1><s2>Paris</s2><s3>FRA</s3><sZ>7 aut.</sZ><sZ>8 aut.</sZ></inist:fA14><country>France</country></affiliation></author><author><name sortKey="Ferguson, Neil M" sort="Ferguson, Neil M" uniqKey="Ferguson N" first="Neil M." last="Ferguson">Neil M. Ferguson</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London</s1><s2>London</s2><s3>GBR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ><sZ>5 aut.</sZ><sZ>9 aut.</sZ></inist:fA14><country>Royaume-Uni</country></affiliation></author></analytic><series><title level="j" type="main">Lancet. Infectious diseases : (print)</title><title level="j" type="abbreviated">Lancet. Infect. dis. : (print)</title><idno type="ISSN">1473-3099</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Lancet. Infectious diseases : (print)</title><title level="j" type="abbreviated">Lancet. Infect. dis. : (print)</title><idno type="ISSN">1473-3099</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Coronavirus</term><term>Epidemic</term><term>Middle East respiratory syndrome</term><term>Quantitative analysis</term><term>Surveillance</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Analyse quantitative</term><term>Epidémie</term><term>Surveillance</term><term>Coronavirus</term><term>Syndrome respiratoire du Moyen-Orient</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Analyse quantitative</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Background The novel Middle East respiratory syndrome coronavirus (MERS-CoV) had, as of Aug 8, 2013, caused 111 virologically confirmed or probable human cases of infection worldwide. We analysed epidemiological and genetic data to assess the extent of human infection, the performance of case detection, and the transmission potential of MERS-CoV with and without control measures. Methods We assembled a comprehensive database of all confirmed and probable cases from public sources and estimated the incubation period and generation time from case cluster data. Using data of numbers of visitors to the Middle East and their duration of stay, we estimated the number of symptomatic cases in the Middle East. We did independent analyses, looking at the growth in incident clusters, the growth in viral population, the reproduction number of cluster index cases, and cluster sizes to characterise the dynamical properties of the epidemic and the transmission scenario. Findings The estimated number of symptomatic cases up to Aug 8, 2013, is 940 (95% CI 290-2200), indicating that at least 62% of human symptomatic cases have not been detected. We find that the case-fatality ratio of primary cases detected via routine surveillance (74%; 95% CI 49-91) is biased upwards because of detection bias; the case-fatality ratio of secondary cases was 20% (7-42). Detection of milder cases (or clinical management) seemed to have improved in recent months. Analysis of human clusters indicated that chains of transmission were not self-sustaining when infection control was implemented, but that Rin the absence of controls was in the range 0?8-1?3. Three independent data sources provide evidence that R cannot be much above 1, with an upper bound of 1?2-1?5. Interpretation By showing that a slowly growing epidemic is underway either in human beings or in an animal reservoir, quantification of uncertainty in transmissibility estimates, and provision of the first estimates of the scale of the epidemic and extent of case detection biases, we provide valuable information for more informed risk assessment. Funding Medical Research Council, Bill & Melinda Gates Foundation, EU FP7, and National Institute of General Medical Sciences.</div></front></TEI><inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>1473-3099</s0></fA01><fA03 i2="1"><s0>Lancet. Infect. dis. : (print)</s0></fA03><fA05><s2>14</s2></fA05><fA06><s2>1</s2></fA06><fA08 i1="01" i2="1" l="ENG"><s1>Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility</s1></fA08><fA11 i1="01" i2="1"><s1>CAUCHEMEZ (Simon)</s1></fA11><fA11 i1="02" i2="1"><s1>FRASER (Christophe)</s1></fA11><fA11 i1="03" i2="1"><s1>VAN KERKHOVE (Maria D.)</s1></fA11><fA11 i1="04" i2="1"><s1>DONNELLY (Christl A.)</s1></fA11><fA11 i1="05" i2="1"><s1>RILEY (Steven)</s1></fA11><fA11 i1="06" i2="1"><s1>RAMBAUT (Andrew)</s1></fA11><fA11 i1="07" i2="1"><s1>ENOUF (Vincent)</s1></fA11><fA11 i1="08" i2="1"><s1>VAN DER WERF (Sylvie)</s1></fA11><fA11 i1="09" i2="1"><s1>FERGUSON (Neil M.)</s1></fA11><fA14 i1="01"><s1>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London</s1><s2>London</s2><s3>GBR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ><sZ>5 aut.</sZ><sZ>9 aut.</sZ></fA14><fA14 i1="02"><s1>Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh</s1><s2>Edinburgh</s2><s3>GBR</s3><sZ>6 aut.</sZ></fA14><fA14 i1="03"><s1>Institut Pasteur, Unit of Molecular Genetics of RNA Viruses, UMR3569 CNRS, Universite Paris Diderot Sorbonne Paris Cité</s1><s2>Paris</s2><s3>FRA</s3><sZ>7 aut.</sZ><sZ>8 aut.</sZ></fA14><fA20><s1>50-56</s1></fA20><fA21><s1>2014</s1></fA21><fA23 i1="01"><s0>ENG</s0></fA23><fA43 i1="01"><s1>INIST</s1><s2>27478</s2><s5>354000500748640140</s5></fA43><fA44><s0>0000</s0><s1>© 2014 INIST-CNRS. All rights reserved.</s1></fA44><fA45><s0>20 ref.</s0></fA45><fA47 i1="01" i2="1"><s0>14-0043018</s0></fA47><fA60><s1>P</s1></fA60><fA61><s0>A</s0></fA61><fA64 i1="01" i2="1"><s0>Lancet. Infectious diseases : (print)</s0></fA64><fA66 i1="01"><s0>GBR</s0></fA66><fC01 i1="01" l="ENG"><s0>Background The novel Middle East respiratory syndrome coronavirus (MERS-CoV) had, as of Aug 8, 2013, caused 111 virologically confirmed or probable human cases of infection worldwide. We analysed epidemiological and genetic data to assess the extent of human infection, the performance of case detection, and the transmission potential of MERS-CoV with and without control measures. Methods We assembled a comprehensive database of all confirmed and probable cases from public sources and estimated the incubation period and generation time from case cluster data. Using data of numbers of visitors to the Middle East and their duration of stay, we estimated the number of symptomatic cases in the Middle East. We did independent analyses, looking at the growth in incident clusters, the growth in viral population, the reproduction number of cluster index cases, and cluster sizes to characterise the dynamical properties of the epidemic and the transmission scenario. Findings The estimated number of symptomatic cases up to Aug 8, 2013, is 940 (95% CI 290-2200), indicating that at least 62% of human symptomatic cases have not been detected. We find that the case-fatality ratio of primary cases detected via routine surveillance (74%; 95% CI 49-91) is biased upwards because of detection bias; the case-fatality ratio of secondary cases was 20% (7-42). Detection of milder cases (or clinical management) seemed to have improved in recent months. Analysis of human clusters indicated that chains of transmission were not self-sustaining when infection control was implemented, but that Rin the absence of controls was in the range 0?8-1?3. Three independent data sources provide evidence that R cannot be much above 1, with an upper bound of 1?2-1?5. Interpretation By showing that a slowly growing epidemic is underway either in human beings or in an animal reservoir, quantification of uncertainty in transmissibility estimates, and provision of the first estimates of the scale of the epidemic and extent of case detection biases, we provide valuable information for more informed risk assessment. Funding Medical Research Council, Bill & Melinda Gates Foundation, EU FP7, and National Institute of General Medical Sciences.</s0></fC01><fC02 i1="01" i2="X"><s0>002B05C02C</s0></fC02><fC03 i1="01" i2="X" l="FRE"><s0>Analyse quantitative</s0><s5>07</s5></fC03><fC03 i1="01" i2="X" l="ENG"><s0>Quantitative analysis</s0><s5>07</s5></fC03><fC03 i1="01" i2="X" l="SPA"><s0>Análisis cuantitativo</s0><s5>07</s5></fC03><fC03 i1="02" i2="X" l="FRE"><s0>Epidémie</s0><s5>08</s5></fC03><fC03 i1="02" i2="X" l="ENG"><s0>Epidemic</s0><s5>08</s5></fC03><fC03 i1="02" i2="X" l="SPA"><s0>Epidemia</s0><s5>08</s5></fC03><fC03 i1="03" i2="X" l="FRE"><s0>Surveillance</s0><s5>09</s5></fC03><fC03 i1="03" i2="X" l="ENG"><s0>Surveillance</s0><s5>09</s5></fC03><fC03 i1="03" i2="X" l="SPA"><s0>Vigilancia</s0><s5>09</s5></fC03><fC03 i1="04" i2="X" l="FRE"><s0>Coronavirus</s0><s2>NW</s2><s5>10</s5></fC03><fC03 i1="04" i2="X" l="ENG"><s0>Coronavirus</s0><s2>NW</s2><s5>10</s5></fC03><fC03 i1="04" i2="X" l="SPA"><s0>Coronavirus</s0><s2>NW</s2><s5>10</s5></fC03><fC03 i1="05" i2="X" l="FRE"><s0>Syndrome respiratoire du Moyen-Orient</s0><s4>CD</s4><s5>96</s5></fC03><fC03 i1="05" i2="X" l="ENG"><s0>Middle East respiratory syndrome</s0><s4>CD</s4><s5>96</s5></fC03><fC07 i1="01" i2="X" l="FRE"><s0>Coronaviridae</s0><s2>NW</s2></fC07><fC07 i1="01" i2="X" l="ENG"><s0>Coronaviridae</s0><s2>NW</s2></fC07><fC07 i1="01" i2="X" l="SPA"><s0>Coronaviridae</s0><s2>NW</s2></fC07><fC07 i1="02" i2="X" l="FRE"><s0>Nidovirales</s0><s2>NW</s2></fC07><fC07 i1="02" i2="X" l="ENG"><s0>Nidovirales</s0><s2>NW</s2></fC07><fC07 i1="02" i2="X" l="SPA"><s0>Nidovirales</s0><s2>NW</s2></fC07><fC07 i1="03" i2="X" l="FRE"><s0>Virus</s0><s2>NW</s2></fC07><fC07 i1="03" i2="X" l="ENG"><s0>Virus</s0><s2>NW</s2></fC07><fC07 i1="03" i2="X" l="SPA"><s0>Virus</s0><s2>NW</s2></fC07><fC07 i1="04" i2="X" l="FRE"><s0>Pathologie de l'appareil respiratoire</s0><s5>37</s5></fC07><fC07 i1="04" i2="X" l="ENG"><s0>Respiratory disease</s0><s5>37</s5></fC07><fC07 i1="04" i2="X" l="SPA"><s0>Aparato respiratorio patología</s0><s5>37</s5></fC07><fC07 i1="05" i2="X" l="FRE"><s0>Virose</s0><s5>38</s5></fC07><fC07 i1="05" i2="X" l="ENG"><s0>Viral disease</s0><s5>38</s5></fC07><fC07 i1="05" i2="X" l="SPA"><s0>Virosis</s0><s5>38</s5></fC07><fC07 i1="06" i2="X" l="FRE"><s0>Infection</s0></fC07><fC07 i1="06" i2="X" l="ENG"><s0>Infection</s0></fC07><fC07 i1="06" i2="X" l="SPA"><s0>Infección</s0></fC07><fN21><s1>048</s1></fN21><fN44 i1="01"><s1>OTO</s1></fN44><fN82><s1>OTO</s1></fN82></pA></standard></inist></record>Pour manipuler ce document sous Unix (Dilib)
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|texte= Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility
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