Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility
Identifieur interne : 000120 ( France/Analysis ); précédent : 000119; suivant : 000121Middle 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
- KwdFr :
- Adolescent, Adulte, Adulte d'âge moyen, Analyse de regroupements, Analyse de survie, Coronavirus (), Coronavirus (génétique), Coronavirus (isolement et purification), Enfant, Enfant d'âge préscolaire, Femelle, Humains, Infections de l'appareil respiratoire (transmission), Infections de l'appareil respiratoire (virologie), Infections de l'appareil respiratoire (épidémiologie), Infections à coronavirus (transmission), Infections à coronavirus (virologie), Infections à coronavirus (épidémiologie), Jeune adulte, Moyen Orient (épidémiologie), Mâle, Nombre de reproduction de base, Sujet âgé, Sujet âgé de 80 ans ou plus, Épidémies, Épidémiosurveillance, Évaluation des risques.
- MESH :
- génétique : Coronavirus.
- isolement et purification : Coronavirus.
- virologie : Infections de l'appareil respiratoire, Infections à coronavirus.
- épidémiologie : Infections de l'appareil respiratoire, Infections à coronavirus, Moyen Orient.
- Pascal (Inist)
- Adolescent, Adulte, Adulte d'âge moyen, Analyse de regroupements, Analyse de survie, Analyse quantitative, Coronavirus, Enfant, Enfant d'âge préscolaire, Epidémie, Femelle, Humains, Jeune adulte, Mâle, Nombre de reproduction de base, Sujet âgé, Sujet âgé de 80 ans ou plus, Surveillance, Coronavirus, Syndrome respiratoire du Moyen-Orient, Épidémies, Épidémiosurveillance, Évaluation des risques.
- Wicri :
- topic : Analyse quantitative.
English descriptors
- KwdEn :
- Adolescent, Adult, Aged, Aged, 80 and over, Basic Reproduction Number, Child, Child, Preschool, Cluster Analysis, Coronavirus, Coronavirus (classification), Coronavirus (genetics), Coronavirus (isolation & purification), Coronavirus Infections (epidemiology), Coronavirus Infections (transmission), Coronavirus Infections (virology), Epidemic, Epidemics, Epidemiological Monitoring, Female, Humans, Male, Middle Aged, Middle East (epidemiology), Middle East respiratory syndrome, Quantitative analysis, Respiratory Tract Infections (epidemiology), Respiratory Tract Infections (transmission), Respiratory Tract Infections (virology), Risk Assessment, Surveillance, Survival Analysis, Young Adult.
- MESH :
- geographic , epidemiology : Middle East.
- classification : Coronavirus.
- epidemiology : Coronavirus Infections, Respiratory Tract Infections.
- genetics : Coronavirus.
- isolation & purification : Coronavirus.
- transmission : Coronavirus Infections, Respiratory Tract Infections.
- virology : Coronavirus Infections, Respiratory Tract Infections.
- Adolescent, Adult, Aged, Aged, 80 and over, Basic Reproduction Number, Child, Child, Preschool, Cluster Analysis, Epidemics, Epidemiological Monitoring, Female, Humans, Male, Middle Aged, Risk Assessment, Survival Analysis, Young Adult.
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.
Url:
Affiliations:
- France, Royaume-Uni
- Angleterre, Grand Londres, Écosse, Île-de-France
- Londres, Paris, Édimbourg
- Université d'Édimbourg
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Pascal:14-0043018Le document en format XML
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Van Kerkhove</name><affiliation wicri:level="3"><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><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"><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><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"><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><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"><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><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"><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><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"><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><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. 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(epidemiology)</term><term>Respiratory Tract Infections (transmission)</term><term>Respiratory Tract Infections (virology)</term><term>Risk Assessment</term><term>Surveillance</term><term>Survival Analysis</term><term>Young Adult</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Adolescent</term><term>Adulte</term><term>Adulte d'âge moyen</term><term>Analyse de regroupements</term><term>Analyse de survie</term><term>Coronavirus ()</term><term>Coronavirus (génétique)</term><term>Coronavirus (isolement et purification)</term><term>Enfant</term><term>Enfant d'âge préscolaire</term><term>Femelle</term><term>Humains</term><term>Infections de l'appareil respiratoire (transmission)</term><term>Infections de l'appareil respiratoire (virologie)</term><term>Infections de l'appareil respiratoire (épidémiologie)</term><term>Infections à coronavirus (transmission)</term><term>Infections à coronavirus (virologie)</term><term>Infections à coronavirus (épidémiologie)</term><term>Jeune adulte</term><term>Moyen Orient (épidémiologie)</term><term>Mâle</term><term>Nombre de reproduction de base</term><term>Sujet âgé</term><term>Sujet âgé de 80 ans ou plus</term><term>Épidémies</term><term>Épidémiosurveillance</term><term>Évaluation des risques</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Middle East</term></keywords><keywords scheme="MESH" qualifier="classification" xml:lang="en"><term>Coronavirus</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Coronavirus Infections</term><term>Respiratory Tract Infections</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Coronavirus</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Coronavirus</term></keywords><keywords scheme="MESH" qualifier="isolation & purification" xml:lang="en"><term>Coronavirus</term></keywords><keywords scheme="MESH" qualifier="isolement et purification" xml:lang="fr"><term>Coronavirus</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Coronavirus Infections</term><term>Respiratory Tract Infections</term></keywords><keywords scheme="MESH" qualifier="virologie" xml:lang="fr"><term>Infections de l'appareil respiratoire</term><term>Infections à coronavirus</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Coronavirus Infections</term><term>Respiratory Tract Infections</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Infections de l'appareil respiratoire</term><term>Infections à coronavirus</term><term>Moyen Orient</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adolescent</term><term>Adult</term><term>Aged</term><term>Aged, 80 and over</term><term>Basic Reproduction Number</term><term>Child</term><term>Child, Preschool</term><term>Cluster Analysis</term><term>Epidemics</term><term>Epidemiological Monitoring</term><term>Female</term><term>Humans</term><term>Male</term><term>Middle Aged</term><term>Risk Assessment</term><term>Survival Analysis</term><term>Young Adult</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Adolescent</term><term>Adulte</term><term>Adulte d'âge moyen</term><term>Analyse de regroupements</term><term>Analyse de survie</term><term>Analyse quantitative</term><term>Coronavirus</term><term>Enfant</term><term>Enfant d'âge préscolaire</term><term>Epidémie</term><term>Femelle</term><term>Humains</term><term>Jeune adulte</term><term>Mâle</term><term>Nombre de reproduction de base</term><term>Sujet âgé</term><term>Sujet âgé de 80 ans ou plus</term><term>Surveillance</term><term>Coronavirus</term><term>Syndrome respiratoire du Moyen-Orient</term><term>Épidémies</term><term>Épidémiosurveillance</term><term>Évaluation des risques</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><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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