Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2)
Identifieur interne : 000197 ( Main/Exploration ); précédent : 000196; suivant : 000198Substantial 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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Le document en format XML
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<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>
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<author><name sortKey="Bickel, P" uniqKey="Bickel P">P. Bickel</name>
</author>
<author><name sortKey="Anderson, J" uniqKey="Anderson J">J. Anderson</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Yang, W" uniqKey="Yang W">W. Yang</name>
</author>
<author><name sortKey="Karspeck, A" uniqKey="Karspeck A">A. Karspeck</name>
</author>
<author><name sortKey="Shaman, J" uniqKey="Shaman J">J. Shaman</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Shaman, J" uniqKey="Shaman J">J. Shaman</name>
</author>
<author><name sortKey="Yang, W" uniqKey="Yang W">W. Yang</name>
</author>
<author><name sortKey="Kandula, S" uniqKey="Kandula S">S. Kandula</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Defelice, N B" uniqKey="Defelice N">N. B. DeFelice</name>
</author>
<author><name sortKey="Little, E" uniqKey="Little E">E. Little</name>
</author>
<author><name sortKey="Campbell, S R" uniqKey="Campbell S">S. R. Campbell</name>
</author>
<author><name sortKey="Shaman, J" uniqKey="Shaman J">J. Shaman</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Reis, J" uniqKey="Reis J">J. Reis</name>
</author>
<author><name sortKey="Shaman, J" uniqKey="Shaman J">J. Shaman</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Diekmann, O" uniqKey="Diekmann O">O. Diekmann</name>
</author>
<author><name sortKey="Heesterbeek, J A X0a P" uniqKey="Heesterbeek J">J. A.
P. Heesterbeek</name>
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<author><name sortKey="Metz, J X0a A" uniqKey="Metz J">J.
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</biblStruct>
<biblStruct><analytic><author><name sortKey="Diekmann, O" uniqKey="Diekmann O">O. Diekmann</name>
</author>
<author><name sortKey="Heesterbeek, J A X0a P" uniqKey="Heesterbeek J">J. A.
P. Heesterbeek</name>
</author>
<author><name sortKey="Roberts, M X0a G" uniqKey="Roberts M">M.
G. Roberts</name>
</author>
</analytic>
</biblStruct>
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</TEI>
<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>
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