Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility
Identifieur interne : 001012 ( Pmc/Checkpoint ); précédent : 001011; suivant : 001013Middle 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 :
- The Lancet Infectious Diseases [ 1473-3099 ] ; 2014.
Abstract
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.
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.
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
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.
Medical Research Council, Bill & Melinda Gates Foundation, EU FP7, and National Institute of General Medical Sciences.
Url:
DOI: 10.1016/S1473-3099(13)70304-9
PubMed: 24239323
PubMed Central: 3895322
Affiliations:
- France, Royaume-Uni
- Angleterre, Grand Londres, Écosse, Île-de-France
- Londres, Paris, Édimbourg
- Université d'Édimbourg
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Van Kerkhove</name><affiliation wicri:level="3"><nlm:aff id="aff1">MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK</nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London</wicri:regionArea><placeName><settlement type="city">Londres</settlement><region type="country">Angleterre</region><region type="région" nuts="1">Grand Londres</region></placeName></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="3"><nlm:aff id="aff1">MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK</nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London</wicri:regionArea><placeName><settlement type="city">Londres</settlement><region type="country">Angleterre</region><region type="région" nuts="1">Grand Londres</region></placeName></affiliation></author><author><name sortKey="Riley, Steven" sort="Riley, Steven" uniqKey="Riley S" first="Steven" last="Riley">Steven Riley</name><affiliation wicri:level="3"><nlm:aff id="aff1">MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK</nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London</wicri:regionArea><placeName><settlement type="city">Londres</settlement><region type="country">Angleterre</region><region type="région" nuts="1">Grand Londres</region></placeName></affiliation></author><author><name sortKey="Rambaut, Andrew" sort="Rambaut, Andrew" uniqKey="Rambaut A" first="Andrew" last="Rambaut">Andrew Rambaut</name><affiliation wicri:level="4"><nlm:aff id="aff2">Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh, UK</nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh</wicri:regionArea><placeName><settlement type="city">Édimbourg</settlement><region type="country">Écosse</region></placeName><orgName type="university">Université d'Édimbourg</orgName></affiliation></author><author><name sortKey="Enouf, Vincent" sort="Enouf, Vincent" uniqKey="Enouf V" first="Vincent" last="Enouf">Vincent Enouf</name><affiliation wicri:level="3"><nlm:aff id="aff3">Institut Pasteur, Unit of Molecular Genetics of RNA Viruses, UMR3569 CNRS, Université Paris Diderot Sorbonne Paris Cité, Paris, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>Institut Pasteur, Unit of Molecular Genetics of RNA Viruses, UMR3569 CNRS, Université Paris Diderot Sorbonne Paris Cité, Paris</wicri:regionArea><placeName><region type="region">Île-de-France</region><region type="old region">Île-de-France</region><settlement type="city">Paris</settlement></placeName></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="3"><nlm:aff id="aff3">Institut Pasteur, Unit of Molecular Genetics of RNA Viruses, UMR3569 CNRS, Université Paris Diderot Sorbonne Paris Cité, Paris, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>Institut Pasteur, Unit of Molecular Genetics of RNA Viruses, UMR3569 CNRS, Université Paris Diderot Sorbonne Paris Cité, Paris</wicri:regionArea><placeName><region type="region">Île-de-France</region><region type="old region">Île-de-France</region><settlement type="city">Paris</settlement></placeName></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="3"><nlm:aff id="aff1">MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK</nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London</wicri:regionArea><placeName><settlement type="city">Londres</settlement><region type="country">Angleterre</region><region type="région" nuts="1">Grand Londres</region></placeName></affiliation></author></analytic><series><title level="j">The Lancet Infectious Diseases</title><idno type="ISSN">1473-3099</idno><idno type="eISSN">1474-4457</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><title>Summary</title><sec><title>Background</title><p>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.</p></sec><sec><title>Methods</title><p>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.</p></sec><sec><title>Findings</title><p>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 <italic>R</italic> in the absence of controls was in the range 0·8–1·3. Three independent data sources provide evidence that <italic>R</italic> cannot be much above 1, with an upper bound of 1·2–1·5.</p></sec><sec><title>Interpretation</title><p>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.</p></sec><sec><title>Funding</title><p>Medical Research Council, Bill & Melinda Gates Foundation, EU FP7, and National Institute of General Medical Sciences.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Hijawi, B" uniqKey="Hijawi B">B Hijawi</name></author><author><name sortKey="Abdallat, M" uniqKey="Abdallat M">M Abdallat</name></author><author><name sortKey="Sayaydeh, A" uniqKey="Sayaydeh A">A 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article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Lancet Infect Dis</journal-id><journal-id journal-id-type="iso-abbrev">Lancet Infect Dis</journal-id><journal-title-group><journal-title>The Lancet Infectious Diseases</journal-title></journal-title-group><issn pub-type="ppub">1473-3099</issn><issn pub-type="epub">1474-4457</issn><publisher><publisher-name>Elsevier Science, The Lancet Pub. Group</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">24239323</article-id><article-id pub-id-type="pmc">3895322</article-id><article-id pub-id-type="publisher-id">S1473-3099(13)70304-9</article-id><article-id pub-id-type="doi">10.1016/S1473-3099(13)70304-9</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group></article-categories><title-group><article-title>Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Cauchemez</surname><given-names>Simon</given-names></name><degrees>PhD</degrees><xref rid="aff1" ref-type="aff">a</xref><xref rid="fn1" ref-type="fn">†</xref></contrib><contrib contrib-type="author"><name><surname>Fraser</surname><given-names>Christophe</given-names></name><degrees>Prof</degrees><degrees>PhD</degrees><xref rid="aff1" ref-type="aff">a</xref><xref rid="fn1" ref-type="fn">†</xref></contrib><contrib contrib-type="author"><name><surname>Van Kerkhove</surname><given-names>Maria D</given-names></name><degrees>PhD</degrees><xref rid="aff1" ref-type="aff">a</xref></contrib><contrib contrib-type="author"><name><surname>Donnelly</surname><given-names>Christl A</given-names></name><degrees>Prof</degrees><degrees>ScD</degrees><xref rid="aff1" ref-type="aff">a</xref></contrib><contrib contrib-type="author"><name><surname>Riley</surname><given-names>Steven</given-names></name><degrees>PhD</degrees><xref rid="aff1" ref-type="aff">a</xref></contrib><contrib contrib-type="author"><name><surname>Rambaut</surname><given-names>Andrew</given-names></name><degrees>Prof</degrees><degrees>PhD</degrees><xref rid="aff2" ref-type="aff">b</xref></contrib><contrib contrib-type="author"><name><surname>Enouf</surname><given-names>Vincent</given-names></name><degrees>PhD</degrees><xref rid="aff3" ref-type="aff">c</xref></contrib><contrib contrib-type="author"><name><surname>van der Werf</surname><given-names>Sylvie</given-names></name><degrees>Prof</degrees><degrees>PhD</degrees><xref rid="aff3" ref-type="aff">c</xref></contrib><contrib contrib-type="author"><name><surname>Ferguson</surname><given-names>Neil M</given-names></name><degrees>Prof</degrees><degrees>DPhil</degrees><email>neil.ferguson@imperial.ac.uk</email><xref rid="aff1" ref-type="aff">a</xref><xref rid="cor1" ref-type="corresp">*</xref></contrib></contrib-group><aff id="aff1"><label>a</label>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK</aff><aff id="aff2"><label>b</label>Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh, UK</aff><aff id="aff3"><label>c</label>Institut Pasteur, Unit of Molecular Genetics of RNA Viruses, UMR3569 CNRS, Université Paris Diderot Sorbonne Paris Cité, Paris, France</aff><author-notes><corresp id="cor1"><label>*</label>Correspondence to: Prof Neil M Ferguson, MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, Norfolk Place, London W2 1PG, UK <email>neil.ferguson@imperial.ac.uk</email></corresp><fn id="fn1"><label>†</label><p>These authors contributed equally to this study</p></fn></author-notes><pub-date pub-type="pmc-release"><day>1</day><month>1</month><year>2014</year></pub-date><pmc-comment> PMC Release delay is 0 months and 0 days and was
based on .</pmc-comment>
<pub-date pub-type="ppub"><month>1</month><year>2014</year></pub-date><volume>14</volume><issue>1</issue><fpage>50</fpage><lpage>56</lpage><permissions><copyright-statement>© 2014 Cauchemez et al. Open Access article distributed under the terms of CC BY</copyright-statement><copyright-year>2014</copyright-year><license><license-p>This document may be redistributed and reused, subject to <ext-link ext-link-type="uri" xlink:href="http://www.elsevier.com/wps/find/authorsview.authors/supplementalterms1.0">certain conditions</ext-link>.</license-p></license></permissions><abstract><title>Summary</title><sec><title>Background</title><p>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.</p></sec><sec><title>Methods</title><p>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.</p></sec><sec><title>Findings</title><p>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 <italic>R</italic> in the absence of controls was in the range 0·8–1·3. Three independent data sources provide evidence that <italic>R</italic> cannot be much above 1, with an upper bound of 1·2–1·5.</p></sec><sec><title>Interpretation</title><p>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.</p></sec><sec><title>Funding</title><p>Medical Research Council, Bill & Melinda Gates Foundation, EU FP7, and National Institute of General Medical Sciences.</p></sec></abstract></article-meta></front><floats-group><fig id="fig1"><label>Figure 1</label><caption><p>Epidemiological and genetic data</p><p>(A) Probability density and cumulative probability of the incubation period from data of exposure for a subset of seven cases. (B) Probability density and cumulative probability of the delay between onset of first and second cases in six case clusters with more than one case. The delay between onset of first and second cases is a lower bound of the generation time. (C) Cumulative number of confirmed cases and clusters detected of MERS-CoV. (D) Maximum likelihood phylogeny of viral sequences of MERS-CoV, obtained using PhyML with the TN93 model. More recent samples were found to cluster together (highlighted in red), suggesting these viruses are part of an emerging epidemic. Only Al-Hasa_1 was included in analysis, to avoid over-representation of this outbreak.</p></caption><graphic xlink:href="gr1"></graphic></fig><fig id="fig2"><label>Figure 2</label><caption><p>Alternative scenarios for animal-to-human and human-to-human transmission</p><p>(A–C) Illustrative epidemic trajectories (incidence of human infections occurring in each transmission generation of length <italic>T<sub>G</sub></italic>=12 days) consistent with the timing of clusters and data on returning non-resident traveller cases for <italic>R</italic><sub>0</sub>=0·3 (A), <italic>R</italic><sub>0</sub>=0·7 (B), and <italic>R</italic><sub>0</sub>=1·06 (C). (D) Proportion of human cases due to human-to-human transmission in the epidemic so far as a function of the reproduction number, for <italic>T<sub>G</sub></italic>=12 days. (E) Probability that current chains of transmission will be sustained for a finite period (1 year) as a function of the reproduction number, for <italic>T<sub>G</sub></italic>=12 days. See <xref rid="sec1" ref-type="sec">appendix</xref> for details.</p></caption><graphic xlink:href="gr2"></graphic></fig><fig id="fig3"><label>Figure 3</label><caption><p>Outcome as a function of month of symptom onset for years 2012–13</p><p>When onset information was missing, the date of symptom onset was estimated by subtracting 10 days (the median delay from onset to reporting in 2013, once the Al Hasa cluster had been excluded) to the date of reporting.</p></caption><graphic xlink:href="gr3"></graphic></fig><boxed-text id="box1"><label>Panel</label><caption><title>Research in context</title></caption><p><bold>Systematic review</bold></p><p>MERS-CoV cases continue to be reported (150 confirmed cases at the time this Article was going to press on Nov 5, 2013), largely in Middle Eastern countries, but by far, the largest number of cases have been reported in Saudi Arabia. Evidence is growing that the MERS-CoV virus, or a closely related virus, has infected camels in Egypt and Qatar, and probably in many other countries throughout the affected region. Without finding the virus in animals, it is impossible to know the reservoir(s) of this virus and stop transmission from animals to man.</p><p>We analysed all publicly available epidemiological data up to Aug 8, 2013, provided by WHO<xref rid="bib7 bib17" ref-type="bibr"><sup>7,17</sup></xref> from 111 virologically confirmed or probable human MERS-CoV cases distributed over the eight affected countries and publicly available genetic data, assessed the extent of human infection, the performance of case detection, and the transmission potential of MERS-CoV with and without control measures. A PubMed search on Sept 24, 2013, with the terms “HCoV-EMC”, “MERS-CoV”, and “novel coronavirus” identified 27, 63, and 279 papers, respectively. All relevant papers are included in this report. We also searched WHO, and the Saudi Arabia Ministry of Health websites and reviewed all publications for MERS-CoV published to date.</p><p><bold>Interpretation</bold></p><p>Our report is the first to estimate the total number of symptomatic cases from returning non-resident traveller cases and to quantify detection biases towards severe cases. Breban and colleagues<xref rid="bib14" ref-type="bibr"><sup>14</sup></xref> found that in clusters that were detected and investigated, the reproduction number was smaller than 1. Since control measures were implemented in many of these clusters, transmission in the absence of control measures remained unknown. We did independent analyses, looking at the growth in incident cases and incident clusters, the growth in viral population, and the reproduction number of cluster index cases to derive upper bounds of <italic>R</italic> in the absence of control measures.</p></boxed-text></floats-group></pmc><affiliations><list><country><li>France</li><li>Royaume-Uni</li></country><region><li>Angleterre</li><li>Grand Londres</li><li>Écosse</li><li>Île-de-France</li></region><settlement><li>Londres</li><li>Paris</li><li>Édimbourg</li></settlement><orgName><li>Université d'Édimbourg</li></orgName></list><tree><country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Cauchemez, Simon" sort="Cauchemez, Simon" uniqKey="Cauchemez S" first="Simon" last="Cauchemez">Simon Cauchemez</name></region><name sortKey="Donnelly, Christl A" sort="Donnelly, Christl A" uniqKey="Donnelly C" first="Christl A" last="Donnelly">Christl A. Donnelly</name><name sortKey="Ferguson, Neil M" sort="Ferguson, Neil M" uniqKey="Ferguson N" first="Neil M" last="Ferguson">Neil M. Ferguson</name><name sortKey="Fraser, Christophe" sort="Fraser, Christophe" uniqKey="Fraser C" first="Christophe" last="Fraser">Christophe Fraser</name><name sortKey="Rambaut, Andrew" sort="Rambaut, Andrew" uniqKey="Rambaut A" first="Andrew" last="Rambaut">Andrew Rambaut</name><name sortKey="Riley, Steven" sort="Riley, Steven" uniqKey="Riley S" first="Steven" last="Riley">Steven Riley</name><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></country><country name="France"><region name="Île-de-France"><name sortKey="Enouf, Vincent" sort="Enouf, Vincent" uniqKey="Enouf V" first="Vincent" last="Enouf">Vincent Enouf</name></region><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></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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