Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2)
Identifieur interne : 000060 ( Pmc/Checkpoint ); précédent : 000059; suivant : 000061Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2)
Auteurs : Ruiyun Li [Royaume-Uni] ; Sen Pei [États-Unis] ; Bin Chen [États-Unis] ; Yimeng Song [Hong Kong] ; Tao Zhang [République populaire de Chine] ; Wan Yang [États-Unis] ; Jeffrey Shaman [États-Unis]Source :
- Science (New York, N.y.) [ 0036-8075 ] ; 2020.
Abstract
Estimation of the prevalence and contagiousness of undocumented novel coronavirus (SARS-CoV2) infections is critical for understanding the overall prevalence and pandemic potential of this disease. Here we use observations of reported infection within China, in conjunction with mobility data, a networked dynamic metapopulation model and Bayesian inference, to infer critical epidemiological characteristics associated with SARS-CoV2, including the fraction of undocumented infections and their contagiousness. We estimate 86% of all infections were undocumented (95% CI: [82%–90%]) prior to 23 January 2020 travel restrictions. Per person, the transmission rate of undocumented infections was 55% of documented infections ([46%–62%]), yet, due to their greater numbers, undocumented infections were the infection source for 79% of documented cases. These findings explain the rapid geographic spread of SARS-CoV2 and indicate containment of this virus will be particularly challenging.
Url:
DOI: 10.1126/science.abb3221
PubMed: 32179701
PubMed Central: 7164387
Affiliations:
- Hong Kong, Royaume-Uni, République populaire de Chine, États-Unis
- Californie, État de New York
- New York, Pékin
- Université Columbia
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novel coronavirus (SARS-CoV2)</title><author><name sortKey="Li, Ruiyun" sort="Li, Ruiyun" uniqKey="Li R" first="Ruiyun" last="Li">Ruiyun Li</name><affiliation wicri:level="1"><nlm:aff id="aff1">MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London W2 1PG, UK.</nlm:aff><country xml:lang="fr" wicri:curation="lc">Royaume-Uni</country><wicri:regionArea>MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London W2 1PG</wicri:regionArea><wicri:noRegion>London W2 1PG</wicri:noRegion></affiliation></author><author><name sortKey="Pei, Sen" sort="Pei, Sen" uniqKey="Pei S" first="Sen" last="Pei">Sen Pei</name><affiliation wicri:level="4"><nlm:aff id="aff2">Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.</nlm:aff><country xml:lang="fr" wicri:curation="lc">États-Unis</country><wicri:regionArea>Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032</wicri:regionArea><placeName><region type="state">État de New York</region><settlement type="city">New York</settlement></placeName><orgName type="university">Université Columbia</orgName></affiliation></author><author><name sortKey="Chen, Bin" sort="Chen, Bin" uniqKey="Chen B" first="Bin" last="Chen">Bin Chen</name><affiliation wicri:level="2"><nlm:aff id="aff3">Department of Land, Air and Water Resources, University of California, Davis, Davis, CA 95616, USA.</nlm:aff><country xml:lang="fr" wicri:curation="lc">États-Unis</country><wicri:regionArea>Department of Land, Air and Water Resources, University of California, Davis, Davis, CA 95616</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Song, Yimeng" sort="Song, Yimeng" uniqKey="Song Y" first="Yimeng" last="Song">Yimeng Song</name><affiliation wicri:level="1"><nlm:aff id="aff4">Department of Urban Planning and Design, The University of Hong Kong, Hong Kong.</nlm:aff><country xml:lang="fr" wicri:curation="lc">Hong Kong</country><wicri:regionArea>Department of Urban Planning and Design, The University of Hong Kong</wicri:regionArea><wicri:noRegion>The University of Hong Kong</wicri:noRegion></affiliation></author><author><name sortKey="Zhang, Tao" sort="Zhang, Tao" uniqKey="Zhang T" first="Tao" last="Zhang">Tao Zhang</name><affiliation wicri:level="1"><nlm:aff id="aff5">Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 10084, P. R. China.</nlm:aff><country xml:lang="fr" wicri:curation="lc">République populaire de Chine</country><wicri:regionArea>Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 10084</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Yang, Wan" sort="Yang, Wan" uniqKey="Yang W" first="Wan" last="Yang">Wan Yang</name><affiliation wicri:level="4"><nlm:aff id="aff6">Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.</nlm:aff><country xml:lang="fr" wicri:curation="lc">États-Unis</country><wicri:regionArea>Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032</wicri:regionArea><placeName><region type="state">État de New York</region><settlement type="city">New York</settlement></placeName><orgName type="university">Université Columbia</orgName></affiliation></author><author><name sortKey="Shaman, Jeffrey" sort="Shaman, Jeffrey" uniqKey="Shaman J" first="Jeffrey" last="Shaman">Jeffrey Shaman</name><affiliation wicri:level="4"><nlm:aff id="aff2">Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.</nlm:aff><country xml:lang="fr" wicri:curation="lc">États-Unis</country><wicri:regionArea>Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032</wicri:regionArea><placeName><region type="state">État de New York</region><settlement type="city">New York</settlement></placeName><orgName type="university">Université Columbia</orgName></affiliation></author></analytic><series><title level="j">Science (New York, N.y.)</title><idno type="ISSN">0036-8075</idno><idno type="eISSN">1095-9203</idno><imprint><date when="2020">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Estimation of the prevalence and contagiousness of undocumented novel coronavirus
(SARS-CoV2) infections is critical for understanding the overall prevalence and pandemic
potential of this disease. Here we use observations of reported infection within China, in
conjunction with mobility data, a networked dynamic metapopulation model and Bayesian
inference, to infer critical epidemiological characteristics associated with SARS-CoV2,
including the fraction of undocumented infections and their contagiousness. We estimate
86% of all infections were undocumented (95% CI: [82%–90%]) prior to 23 January
2020 travel restrictions. Per person, the transmission rate of undocumented infections was
55% of documented infections ([46%–62%]), yet, due to their greater numbers,
undocumented infections were the infection source for 79% of documented cases. These
findings explain the rapid geographic spread of SARS-CoV2 and indicate containment of this
virus will be particularly challenging.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Chan, J F" uniqKey="Chan J">J. F. Chan</name></author><author><name sortKey="Yuan, S" uniqKey="Yuan S">S. Yuan</name></author><author><name sortKey="Kok, K H" uniqKey="Kok K">K. H. Kok</name></author><author><name sortKey="To, K K" uniqKey="To K">K. K. To</name></author><author><name sortKey="Chu, H" uniqKey="Chu H">H. Chu</name></author><author><name sortKey="Yang, J" uniqKey="Yang J">J. Yang</name></author><author><name sortKey="Xing, F" uniqKey="Xing F">F. Xing</name></author><author><name sortKey="Liu, J" uniqKey="Liu J">J. Liu</name></author><author><name sortKey="Yip, C C" uniqKey="Yip C">C. C. Yip</name></author><author><name sortKey="Poon, R W" uniqKey="Poon R">R. W. Poon</name></author><author><name sortKey="Tsoi, H W" uniqKey="Tsoi H">H. W. Tsoi</name></author><author><name sortKey="Lo, S K" uniqKey="Lo S">S. K. Lo</name></author><author><name sortKey="Chan, K H" uniqKey="Chan K">K. H. Chan</name></author><author><name sortKey="Poon, V K" uniqKey="Poon V">V. K. Poon</name></author><author><name sortKey="Chan, W M" uniqKey="Chan W">W. M. Chan</name></author><author><name sortKey="Ip, J D" uniqKey="Ip J">J. D. Ip</name></author><author><name sortKey="Cai, J P" uniqKey="Cai J">J. P. Cai</name></author><author><name sortKey="Cheng, V C" uniqKey="Cheng V">V. C. Cheng</name></author><author><name sortKey="Chen, H" uniqKey="Chen H">H. Chen</name></author><author><name sortKey="Hui, C K" uniqKey="Hui C">C. K. Hui</name></author><author><name sortKey="Yuen, K Y" uniqKey="Yuen K">K. Y. Yuen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wu, P" uniqKey="Wu P">P. Wu</name></author><author><name sortKey="Hao, X" uniqKey="Hao X">X. Hao</name></author><author><name sortKey="Lau, E H Y" uniqKey="Lau E">E. H. Y. Lau</name></author><author><name sortKey="Wong, J Y" uniqKey="Wong J">J. Y. Wong</name></author><author><name sortKey="Leung, K S X0a M" uniqKey="Leung K">K. S.
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G. Roberts</name></author></analytic></biblStruct><biblStruct></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">Science</journal-id><journal-id journal-id-type="iso-abbrev">Science</journal-id><journal-id journal-id-type="publisher-id">SCIENCE</journal-id><journal-title-group><journal-title>Science (New York, N.y.)</journal-title></journal-title-group><issn pub-type="ppub">0036-8075</issn><issn pub-type="epub">1095-9203</issn><publisher><publisher-name>American Association for the Advancement of Science</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">32179701</article-id><article-id pub-id-type="pmc">7164387</article-id><article-id pub-id-type="publisher-id">abb3221</article-id><article-id pub-id-type="doi">10.1126/science.abb3221</article-id><article-categories><subj-group subj-group-type="article-type"><subject>Research Article</subject></subj-group><subj-group subj-group-type="heading"><subject>Research Articles</subject></subj-group><subj-group subj-group-type="legacy-article-type"><subject>R-Articles</subject></subj-group><subj-group subj-group-type="field"><subject>Epidemiology</subject></subj-group></article-categories><title-group><article-title>Substantial undocumented infection facilitates the rapid dissemination of
novel coronavirus (SARS-CoV2)</article-title></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="true">https://orcid.org/0000-0001-8927-9965</contrib-id><name><surname>Li</surname><given-names>Ruiyun</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="author-notes" rid="afn1">*</xref></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="true">https://orcid.org/0000-0002-7072-2995</contrib-id><name><surname>Pei</surname><given-names>Sen</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="author-notes" rid="afn1">*</xref><xref ref-type="corresp" rid="cor1">†</xref></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="true">https://orcid.org/0000-0003-3496-2876</contrib-id><name><surname>Chen</surname><given-names>Bin</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref><xref ref-type="author-notes" rid="afn1">*</xref></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="true">https://orcid.org/0000-0001-9558-1220</contrib-id><name><surname>Song</surname><given-names>Yimeng</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author"><name><surname>Zhang</surname><given-names>Tao</given-names></name><xref ref-type="aff" rid="aff5"><sup>5</sup></xref></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="true">https://orcid.org/0000-0002-7555-9728</contrib-id><name><surname>Yang</surname><given-names>Wan</given-names></name><xref ref-type="award" rid="award587412"></xref><xref ref-type="aff" rid="aff6"><sup>6</sup></xref></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="true">https://orcid.org/0000-0002-7216-7809</contrib-id><name><surname>Shaman</surname><given-names>Jeffrey</given-names></name><xref ref-type="award" rid="award587411"></xref><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="corresp" rid="cor1">†</xref></contrib><aff id="aff1"><label>1</label>MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London W2 1PG, UK.</aff><aff id="aff2"><label>2</label>Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.</aff><aff id="aff3"><label>3</label>Department of Land, Air and Water Resources, University of California, Davis, Davis, CA 95616, USA.</aff><aff id="aff4"><label>4</label>Department of Urban Planning and Design, The University of Hong Kong, Hong Kong.</aff><aff id="aff5"><label>5</label>Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 10084, P. R. China.</aff><aff id="aff6"><label>6</label>Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.</aff></contrib-group><author-notes><fn id="afn1" fn-type="equal"><label>*</label><p>These authors contributed equally to this work.</p></fn><corresp id="cor1"><label>†</label>Corresponding author. Email: <email xlink:href="sp3449@cumc.columbia.edu">sp3449@cumc.columbia.edu</email> (S.P.); <email xlink:href="jls106@cumc.columbia.edu">jls106@cumc.columbia.edu</email> (J.S.)</corresp></author-notes><pub-date pub-type="epub"><day>16</day><month>3</month><year>2020</year></pub-date><elocation-id>eabb3221</elocation-id><history><date date-type="received"><day>15</day><month>2</month><year>2020</year></date><date date-type="accepted"><day>12</day><month>3</month><year>2020</year></date></history><permissions><copyright-statement>Copyright © 2020, American Association for the Advancement of
Science</copyright-statement><copyright-year>2020</copyright-year><copyright-holder>American Association for the Advancement of Science</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0/"><ali:license_ref specific-use="vor" start_date="2020-03-04">https://creativecommons.org/licenses/by/4.0/</ali:license_ref><license-p>This open access article is distributed under <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License 4.0 (CC BY)</ext-link>.</license-p></license></permissions><abstract><p>Estimation of the prevalence and contagiousness of undocumented novel coronavirus
(SARS-CoV2) infections is critical for understanding the overall prevalence and pandemic
potential of this disease. Here we use observations of reported infection within China, in
conjunction with mobility data, a networked dynamic metapopulation model and Bayesian
inference, to infer critical epidemiological characteristics associated with SARS-CoV2,
including the fraction of undocumented infections and their contagiousness. We estimate
86% of all infections were undocumented (95% CI: [82%–90%]) prior to 23 January
2020 travel restrictions. Per person, the transmission rate of undocumented infections was
55% of documented infections ([46%–62%]), yet, due to their greater numbers,
undocumented infections were the infection source for 79% of documented cases. These
findings explain the rapid geographic spread of SARS-CoV2 and indicate containment of this
virus will be particularly challenging.</p></abstract><funding-group><award-group id="award587411"><funding-source><institution-wrap><institution-id institution-id-type="doi">http://dx.doi.org/10.13039/100000057</institution-id><institution>National Institute of General Medical Sciences</institution></institution-wrap></funding-source><award-id>GM110748</award-id></award-group><award-group id="award587412"><funding-source><institution-wrap><institution-id institution-id-type="doi">http://dx.doi.org/10.13039/100000060</institution-id><institution>National Institute of Allergy and Infectious Diseases</institution></institution-wrap></funding-source><award-id>AI145883</award-id></award-group></funding-group><custom-meta-group><custom-meta><meta-name>Number-color-figs</meta-name><meta-value>2</meta-value></custom-meta><custom-meta><meta-name>Number-figs</meta-name><meta-value>2</meta-value></custom-meta></custom-meta-group></article-meta></front></pmc><affiliations><list><country><li>Hong Kong</li><li>Royaume-Uni</li><li>République populaire de Chine</li><li>États-Unis</li></country><region><li>Californie</li><li>État de New York</li></region><settlement><li>New York</li><li>Pékin</li></settlement><orgName><li>Université Columbia</li></orgName></list><tree><country name="Royaume-Uni"><noRegion><name sortKey="Li, Ruiyun" sort="Li, Ruiyun" uniqKey="Li R" first="Ruiyun" last="Li">Ruiyun Li</name></noRegion></country><country name="États-Unis"><region name="État de New York"><name sortKey="Pei, Sen" sort="Pei, Sen" uniqKey="Pei S" first="Sen" last="Pei">Sen Pei</name></region><name sortKey="Chen, Bin" sort="Chen, Bin" uniqKey="Chen B" first="Bin" last="Chen">Bin Chen</name><name sortKey="Shaman, Jeffrey" sort="Shaman, Jeffrey" uniqKey="Shaman J" first="Jeffrey" last="Shaman">Jeffrey Shaman</name><name sortKey="Yang, Wan" sort="Yang, Wan" uniqKey="Yang W" first="Wan" last="Yang">Wan Yang</name></country><country name="Hong Kong"><noRegion><name sortKey="Song, Yimeng" sort="Song, Yimeng" uniqKey="Song Y" first="Yimeng" last="Song">Yimeng Song</name></noRegion></country><country name="République populaire de Chine"><noRegion><name sortKey="Zhang, Tao" sort="Zhang, Tao" uniqKey="Zhang T" first="Tao" last="Zhang">Tao Zhang</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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