File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2)

TitleSubstantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2)
Authors
KeywordsBayes theorem
China
conceptual framework
coronavirus disease 2019
data analysis
Issue Date2020
PublisherAmerican Association for the Advancement of Science. The Journal's web site is located at http://sciencemag.org
Citation
Science, 2020, v. 368 n. 6490, p. 489-493 How to Cite?
AbstractEstimation of the prevalence and contagiousness of undocumented novel coronavirus [severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2)] 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-CoV-2, including the fraction of undocumented infections and their contagiousness. We estimate that 86% of all infections were undocumented [95% credible interval (CI): 82–90%] before the 23 January 2020 travel restrictions. The transmission rate of undocumented infections per person was 55% the transmission rate of documented infections (95% CI: 46–62%), yet, because of their greater numbers, undocumented infections were the source of 79% of the documented cases. These findings explain the rapid geographic spread of SARS-CoV-2 and indicate that containment of this virus will be particularly challenging.
Persistent Identifierhttp://hdl.handle.net/10722/291076
ISSN
2021 Impact Factor: 63.714
2020 SCImago Journal Rankings: 12.556
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, R-
dc.contributor.authorPei, S-
dc.contributor.authorChen, B-
dc.contributor.authorSong, Y-
dc.contributor.authorZhang, T-
dc.contributor.authorYang, W-
dc.contributor.authorShaman, J-
dc.date.accessioned2020-11-02T05:51:13Z-
dc.date.available2020-11-02T05:51:13Z-
dc.date.issued2020-
dc.identifier.citationScience, 2020, v. 368 n. 6490, p. 489-493-
dc.identifier.issn0036-8075-
dc.identifier.urihttp://hdl.handle.net/10722/291076-
dc.description.abstractEstimation of the prevalence and contagiousness of undocumented novel coronavirus [severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2)] 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-CoV-2, including the fraction of undocumented infections and their contagiousness. We estimate that 86% of all infections were undocumented [95% credible interval (CI): 82–90%] before the 23 January 2020 travel restrictions. The transmission rate of undocumented infections per person was 55% the transmission rate of documented infections (95% CI: 46–62%), yet, because of their greater numbers, undocumented infections were the source of 79% of the documented cases. These findings explain the rapid geographic spread of SARS-CoV-2 and indicate that containment of this virus will be particularly challenging.-
dc.languageeng-
dc.publisherAmerican Association for the Advancement of Science. The Journal's web site is located at http://sciencemag.org-
dc.relation.ispartofScience-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectBayes theorem-
dc.subjectChina-
dc.subjectconceptual framework-
dc.subjectcoronavirus disease 2019-
dc.subjectdata analysis-
dc.titleSubstantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2)-
dc.typeArticle-
dc.identifier.emailSong, Y: ymsong@hku.hk-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1126/science.abb3221-
dc.identifier.pmid32179701-
dc.identifier.pmcidPMC7164387-
dc.identifier.scopuseid_2-s2.0-85082462003-
dc.identifier.hkuros318545-
dc.identifier.volume368-
dc.identifier.issue6490-
dc.identifier.spage489-
dc.identifier.epage493-
dc.identifier.isiWOS:000531178400040-
dc.publisher.placeUnited States-
dc.identifier.f1000737557783-
dc.identifier.issnl0036-8075-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats