Early dynamics of transmission and control of COVID-19: a mathematical modelling study.
Identifieur interne : 000006 ( PubMed/Corpus ); précédent : 000005; suivant : 000007Early dynamics of transmission and control of COVID-19: a mathematical modelling study.
Auteurs : Adam J. Kucharski ; Timothy W. Russell ; Charlie Diamond ; Yang Liu ; John Edmunds ; Sebastian Funk ; Rosalind M. EggoSource :
- The Lancet. Infectious diseases [ 1474-4457 ] ; 2020.
Abstract
An outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to 95 333 confirmed cases as of March 5, 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. Combining a mathematical model of severe SARS-CoV-2 transmission with four datasets from within and outside Wuhan, we estimated how transmission in Wuhan varied between December, 2019, and February, 2020. We used these estimates to assess the potential for sustained human-to-human transmission to occur in locations outside Wuhan if cases were introduced.
DOI: 10.1016/S1473-3099(20)30144-4
PubMed: 32171059
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Early dynamics of transmission and control of COVID-19: a mathematical modelling study.</title><author><name sortKey="Kucharski, Adam J" sort="Kucharski, Adam J" uniqKey="Kucharski A" first="Adam J" last="Kucharski">Adam J. Kucharski</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK. Electronic address: adam.kucharski@lshtm.ac.uk.</nlm:affiliation></affiliation></author><author><name sortKey="Russell, Timothy W" sort="Russell, Timothy W" uniqKey="Russell T" first="Timothy W" last="Russell">Timothy W. Russell</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Diamond, Charlie" sort="Diamond, Charlie" uniqKey="Diamond C" first="Charlie" last="Diamond">Charlie Diamond</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Liu, Yang" sort="Liu, Yang" uniqKey="Liu Y" first="Yang" last="Liu">Yang Liu</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Edmunds, John" sort="Edmunds, John" uniqKey="Edmunds J" first="John" last="Edmunds">John Edmunds</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Funk, Sebastian" sort="Funk, Sebastian" uniqKey="Funk S" first="Sebastian" last="Funk">Sebastian Funk</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Eggo, Rosalind M" sort="Eggo, Rosalind M" uniqKey="Eggo R" first="Rosalind M" last="Eggo">Rosalind M. Eggo</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:32171059</idno><idno type="pmid">32171059</idno><idno type="doi">10.1016/S1473-3099(20)30144-4</idno><idno type="wicri:Area/PubMed/Corpus">000006</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000006</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Early dynamics of transmission and control of COVID-19: a mathematical modelling study.</title><author><name sortKey="Kucharski, Adam J" sort="Kucharski, Adam J" uniqKey="Kucharski A" first="Adam J" last="Kucharski">Adam J. Kucharski</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK. Electronic address: adam.kucharski@lshtm.ac.uk.</nlm:affiliation></affiliation></author><author><name sortKey="Russell, Timothy W" sort="Russell, Timothy W" uniqKey="Russell T" first="Timothy W" last="Russell">Timothy W. Russell</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Diamond, Charlie" sort="Diamond, Charlie" uniqKey="Diamond C" first="Charlie" last="Diamond">Charlie Diamond</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Liu, Yang" sort="Liu, Yang" uniqKey="Liu Y" first="Yang" last="Liu">Yang Liu</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Edmunds, John" sort="Edmunds, John" uniqKey="Edmunds J" first="John" last="Edmunds">John Edmunds</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Funk, Sebastian" sort="Funk, Sebastian" uniqKey="Funk S" first="Sebastian" last="Funk">Sebastian Funk</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Eggo, Rosalind M" sort="Eggo, Rosalind M" uniqKey="Eggo R" first="Rosalind M" last="Eggo">Rosalind M. Eggo</name><affiliation><nlm:affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</nlm:affiliation></affiliation></author></analytic><series><title level="j">The Lancet. Infectious diseases</title><idno type="eISSN">1474-4457</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">An outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to 95 333 confirmed cases as of March 5, 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. Combining a mathematical model of severe SARS-CoV-2 transmission with four datasets from within and outside Wuhan, we estimated how transmission in Wuhan varied between December, 2019, and February, 2020. We used these estimates to assess the potential for sustained human-to-human transmission to occur in locations outside Wuhan if cases were introduced.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32171059</PMID><DateRevised><Year>2020</Year><Month>03</Month><Day>14</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1474-4457</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2020</Year><Month>Mar</Month><Day>11</Day></PubDate></JournalIssue><Title>The Lancet. Infectious diseases</Title><ISOAbbreviation>Lancet Infect Dis</ISOAbbreviation></Journal><ArticleTitle>Early dynamics of transmission and control of COVID-19: a mathematical modelling study.</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">S1473-3099(20)30144-4</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1016/S1473-3099(20)30144-4</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">An outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to 95 333 confirmed cases as of March 5, 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. Combining a mathematical model of severe SARS-CoV-2 transmission with four datasets from within and outside Wuhan, we estimated how transmission in Wuhan varied between December, 2019, and February, 2020. We used these estimates to assess the potential for sustained human-to-human transmission to occur in locations outside Wuhan if cases were introduced.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">We combined a stochastic transmission model with data on cases of coronavirus disease 2019 (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January, 2020, and February, 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas. To estimate the early dynamics of transmission in Wuhan, we fitted a stochastic transmission dynamic model to multiple publicly available datasets on cases in Wuhan and internationally exported cases from Wuhan. The four datasets we fitted to were: daily number of new internationally exported cases (or lack thereof), by date of onset, as of Jan 26, 2020; daily number of new cases in Wuhan with no market exposure, by date of onset, between Dec 1, 2019, and Jan 1, 2020; daily number of new cases in China, by date of onset, between Dec 29, 2019, and Jan 23, 2020; and proportion of infected passengers on evacuation flights between Jan 29, 2020, and Feb 4, 2020. We used an additional two datasets for comparison with model outputs: daily number of new exported cases from Wuhan (or lack thereof) in countries with high connectivity to Wuhan (ie, top 20 most at-risk countries), by date of confirmation, as of Feb 10, 2020; and data on new confirmed cases reported in Wuhan between Jan 16, 2020, and Feb 11, 2020.</AbstractText><AbstractText Label="FINDINGS" NlmCategory="RESULTS">We estimated that the median daily reproduction number (R<sub>t</sub>) in Wuhan declined from 2·35 (95% CI 1·15-4·77) 1 week before travel restrictions were introduced on Jan 23, 2020, to 1·05 (0·41-2·39) 1 week after. Based on our estimates of R<sub>t</sub>, assuming SARS-like variation, we calculated that in locations with similar transmission potential to Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population.</AbstractText><AbstractText Label="INTERPRETATION" NlmCategory="CONCLUSIONS">Our results show that COVID-19 transmission probably declined in Wuhan during late January, 2020, coinciding with the introduction of travel control measures. As more cases arrive in international locations with similar transmission potential to Wuhan before these control measures, it is likely many chains of transmission will fail to establish initially, but might lead to new outbreaks eventually.</AbstractText><AbstractText Label="FUNDING" NlmCategory="BACKGROUND">Wellcome Trust, Health Data Research UK, Bill & Melinda Gates Foundation, and National Institute for Health Research.</AbstractText><CopyrightInformation>Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Kucharski</LastName><ForeName>Adam J</ForeName><Initials>AJ</Initials><AffiliationInfo><Affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK. Electronic address: adam.kucharski@lshtm.ac.uk.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Russell</LastName><ForeName>Timothy W</ForeName><Initials>TW</Initials><AffiliationInfo><Affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Diamond</LastName><ForeName>Charlie</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Liu</LastName><ForeName>Yang</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Edmunds</LastName><ForeName>John</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Funk</LastName><ForeName>Sebastian</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Eggo</LastName><ForeName>Rosalind M</ForeName><Initials>RM</Initials><AffiliationInfo><Affiliation>Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><CollectiveName>Centre for Mathematical Modelling of Infectious Diseases COVID-19 working 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