Serveur d'exploration MERS

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Unraveling the drivers of MERS-CoV transmission.

Identifieur interne : 000E58 ( PubMed/Checkpoint ); précédent : 000E57; suivant : 000E59

Unraveling the drivers of MERS-CoV transmission.

Auteurs : Simon Cauchemez [France] ; Pierre Nouvellet [Royaume-Uni] ; Anne Cori [Royaume-Uni] ; Thibaut Jombart [Royaume-Uni] ; Tini Garske [Royaume-Uni] ; Hannah Clapham [États-Unis] ; Sean Moore [États-Unis] ; Harriet Linden Mills [Royaume-Uni] ; Henrik Salje [États-Unis] ; Caitlin Collins [Royaume-Uni] ; Isabel Rodriquez-Barraquer [États-Unis] ; Steven Riley [Royaume-Uni] ; Shaun Truelove [États-Unis] ; Homoud Algarni ; Rafat Alhakeem ; Khalid Alharbi ; Abdulhafiz Turkistani ; Ricardo J. Aguas [Royaume-Uni] ; Derek A T. Cummings [États-Unis] ; Maria D. Van Kerkhove [France] ; Christl A. Donnelly [Royaume-Uni] ; Justin Lessler [États-Unis] ; Christophe Fraser [Royaume-Uni] ; Ali Al-Barrak [Royaume-Uni] ; Neil M. Ferguson [Royaume-Uni]

Source :

RBID : pubmed:27457935

Descripteurs français

English descriptors

Abstract

With more than 1,700 laboratory-confirmed infections, Middle East respiratory syndrome coronavirus (MERS-CoV) remains a significant threat for public health. However, the lack of detailed data on modes of transmission from the animal reservoir and between humans means that the drivers of MERS-CoV epidemics remain poorly characterized. Here, we develop a statistical framework to provide a comprehensive analysis of the transmission patterns underlying the 681 MERS-CoV cases detected in the Kingdom of Saudi Arabia (KSA) between January 2013 and July 2014. We assess how infections from the animal reservoir, the different levels of mixing, and heterogeneities in transmission have contributed to the buildup of MERS-CoV epidemics in KSA. We estimate that 12% [95% credible interval (CI): 9%, 15%] of cases were infected from the reservoir, the rest via human-to-human transmission in clusters (60%; CI: 57%, 63%), within (23%; CI: 20%, 27%), or between (5%; CI: 2%, 8%) regions. The reproduction number at the start of a cluster was 0.45 (CI: 0.33, 0.58) on average, but with large SD (0.53; CI: 0.35, 0.78). It was >1 in 12% (CI: 6%, 18%) of clusters but fell by approximately one-half (47% CI: 34%, 63%) its original value after 10 cases on average. The ongoing exposure of humans to MERS-CoV from the reservoir is of major concern, given the continued risk of substantial outbreaks in health care systems. The approach we present allows the study of infectious disease transmission when data linking cases to each other remain limited and uncertain.

DOI: 10.1073/pnas.1519235113
PubMed: 27457935


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pubmed:27457935

Le document en format XML

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<name sortKey="Rodriquez Barraquer, Isabel" sort="Rodriquez Barraquer, Isabel" uniqKey="Rodriquez Barraquer I" first="Isabel" last="Rodriquez-Barraquer">Isabel Rodriquez-Barraquer</name>
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<nlm:affiliation>Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205;</nlm:affiliation>
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<region type="state">Maryland</region>
</placeName>
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<author>
<name sortKey="Riley, Steven" sort="Riley, Steven" uniqKey="Riley S" first="Steven" last="Riley">Steven Riley</name>
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<nlm:affiliation>Medical Research Council Centre for Outbreak Analysis and Modelling, Imperial College London, Faculty of Medicine, London W2 1PG, United Kingdom;</nlm:affiliation>
<country xml:lang="fr">Royaume-Uni</country>
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<author>
<name sortKey="Truelove, Shaun" sort="Truelove, Shaun" uniqKey="Truelove S" first="Shaun" last="Truelove">Shaun Truelove</name>
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<nlm:affiliation>Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205;</nlm:affiliation>
<country xml:lang="fr">États-Unis</country>
<placeName>
<region type="state">Maryland</region>
</placeName>
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<author>
<name sortKey="Algarni, Homoud" sort="Algarni, Homoud" uniqKey="Algarni H" first="Homoud" last="Algarni">Homoud Algarni</name>
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<author>
<name sortKey="Alhakeem, Rafat" sort="Alhakeem, Rafat" uniqKey="Alhakeem R" first="Rafat" last="Alhakeem">Rafat Alhakeem</name>
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<name sortKey="Alharbi, Khalid" sort="Alharbi, Khalid" uniqKey="Alharbi K" first="Khalid" last="Alharbi">Khalid Alharbi</name>
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<name sortKey="Turkistani, Abdulhafiz" sort="Turkistani, Abdulhafiz" uniqKey="Turkistani A" first="Abdulhafiz" last="Turkistani">Abdulhafiz Turkistani</name>
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<name sortKey="Aguas, Ricardo J" sort="Aguas, Ricardo J" uniqKey="Aguas R" first="Ricardo J" last="Aguas">Ricardo J. Aguas</name>
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<author>
<name sortKey="Cummings, Derek A T" sort="Cummings, Derek A T" uniqKey="Cummings D" first="Derek A T" last="Cummings">Derek A T. Cummings</name>
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<nlm:affiliation>Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205; Department of Biology, University of Florida, Gainesville, FL 32610; Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610;</nlm:affiliation>
<country xml:lang="fr">États-Unis</country>
<placeName>
<region type="state">Floride</region>
</placeName>
<wicri:cityArea>Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205; Department of Biology, University of Florida, Gainesville, FL 32610; Emerging Pathogens Institute, University of Florida, Gainesville</wicri:cityArea>
</affiliation>
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<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>
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<country xml:lang="fr">France</country>
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<region type="region" nuts="2">Île-de-France</region>
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<name sortKey="Donnelly, Christl A" sort="Donnelly, Christl A" uniqKey="Donnelly C" first="Christl A" last="Donnelly">Christl A. Donnelly</name>
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<name sortKey="Lessler, Justin" sort="Lessler, Justin" uniqKey="Lessler J" first="Justin" last="Lessler">Justin Lessler</name>
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<nlm:affiliation>Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205;</nlm:affiliation>
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<placeName>
<region type="state">Maryland</region>
</placeName>
<wicri:cityArea>Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore</wicri:cityArea>
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<name sortKey="Fraser, Christophe" sort="Fraser, Christophe" uniqKey="Fraser C" first="Christophe" last="Fraser">Christophe Fraser</name>
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<name sortKey="Al Barrak, Ali" sort="Al Barrak, Ali" uniqKey="Al Barrak A" first="Ali" last="Al-Barrak">Ali Al-Barrak</name>
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<nlm:affiliation>Ministry of Health, Riyadh 12234, Kingdom of Saudi Arabia; neil.ferguson@imperial.ac.uk ambarrak@moh.gov.sa.</nlm:affiliation>
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<name sortKey="Ferguson, Neil M" sort="Ferguson, Neil M" uniqKey="Ferguson N" first="Neil M" last="Ferguson">Neil M. Ferguson</name>
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<title level="j">Proceedings of the National Academy of Sciences of the United States of America</title>
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<term>Animals</term>
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<term>Disease Reservoirs</term>
<term>Humans</term>
<term>Zoonoses (transmission)</term>
</keywords>
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<term>Animaux</term>
<term>Humains</term>
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<term>Réservoirs d'agents pathogènes</term>
<term>Zoonoses (transmission)</term>
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<term>Coronavirus Infections</term>
<term>Zoonoses</term>
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<term>Animals</term>
<term>Disease Reservoirs</term>
<term>Humans</term>
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<term>Animaux</term>
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<div type="abstract" xml:lang="en">With more than 1,700 laboratory-confirmed infections, Middle East respiratory syndrome coronavirus (MERS-CoV) remains a significant threat for public health. However, the lack of detailed data on modes of transmission from the animal reservoir and between humans means that the drivers of MERS-CoV epidemics remain poorly characterized. Here, we develop a statistical framework to provide a comprehensive analysis of the transmission patterns underlying the 681 MERS-CoV cases detected in the Kingdom of Saudi Arabia (KSA) between January 2013 and July 2014. We assess how infections from the animal reservoir, the different levels of mixing, and heterogeneities in transmission have contributed to the buildup of MERS-CoV epidemics in KSA. We estimate that 12% [95% credible interval (CI): 9%, 15%] of cases were infected from the reservoir, the rest via human-to-human transmission in clusters (60%; CI: 57%, 63%), within (23%; CI: 20%, 27%), or between (5%; CI: 2%, 8%) regions. The reproduction number at the start of a cluster was 0.45 (CI: 0.33, 0.58) on average, but with large SD (0.53; CI: 0.35, 0.78). It was >1 in 12% (CI: 6%, 18%) of clusters but fell by approximately one-half (47% CI: 34%, 63%) its original value after 10 cases on average. The ongoing exposure of humans to MERS-CoV from the reservoir is of major concern, given the continued risk of substantial outbreaks in health care systems. The approach we present allows the study of infectious disease transmission when data linking cases to each other remain limited and uncertain.</div>
</front>
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<DateCompleted>
<Year>2018</Year>
<Month>01</Month>
<Day>29</Day>
</DateCompleted>
<DateRevised>
<Year>2018</Year>
<Month>11</Month>
<Day>13</Day>
</DateRevised>
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<ISSN IssnType="Electronic">1091-6490</ISSN>
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<Volume>113</Volume>
<Issue>32</Issue>
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<Year>2016</Year>
<Month>08</Month>
<Day>09</Day>
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<Title>Proceedings of the National Academy of Sciences of the United States of America</Title>
<ISOAbbreviation>Proc. Natl. Acad. Sci. U.S.A.</ISOAbbreviation>
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<ArticleTitle>Unraveling the drivers of MERS-CoV transmission.</ArticleTitle>
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<MedlinePgn>9081-6</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1073/pnas.1519235113</ELocationID>
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<AbstractText>With more than 1,700 laboratory-confirmed infections, Middle East respiratory syndrome coronavirus (MERS-CoV) remains a significant threat for public health. However, the lack of detailed data on modes of transmission from the animal reservoir and between humans means that the drivers of MERS-CoV epidemics remain poorly characterized. Here, we develop a statistical framework to provide a comprehensive analysis of the transmission patterns underlying the 681 MERS-CoV cases detected in the Kingdom of Saudi Arabia (KSA) between January 2013 and July 2014. We assess how infections from the animal reservoir, the different levels of mixing, and heterogeneities in transmission have contributed to the buildup of MERS-CoV epidemics in KSA. We estimate that 12% [95% credible interval (CI): 9%, 15%] of cases were infected from the reservoir, the rest via human-to-human transmission in clusters (60%; CI: 57%, 63%), within (23%; CI: 20%, 27%), or between (5%; CI: 2%, 8%) regions. The reproduction number at the start of a cluster was 0.45 (CI: 0.33, 0.58) on average, but with large SD (0.53; CI: 0.35, 0.78). It was >1 in 12% (CI: 6%, 18%) of clusters but fell by approximately one-half (47% CI: 34%, 63%) its original value after 10 cases on average. The ongoing exposure of humans to MERS-CoV from the reservoir is of major concern, given the continued risk of substantial outbreaks in health care systems. The approach we present allows the study of infectious disease transmission when data linking cases to each other remain limited and uncertain.</AbstractText>
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