The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak.
Identifieur interne : 000756 ( PubMed/Curation ); précédent : 000755; suivant : 000757The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak.
Auteurs : Matteo Chinazzi [États-Unis] ; Jessica T. Davis [États-Unis] ; Marco Ajelli [Italie] ; Corrado Gioannini [Italie] ; Maria Litvinova [Italie] ; Stefano Merler [Italie] ; Ana Pastore Y Piontti [États-Unis] ; Kunpeng Mu [États-Unis] ; Luca Rossi [Italie] ; Kaiyuan Sun [États-Unis] ; Cécile Viboud [États-Unis] ; Xinyue Xiong [États-Unis] ; Hongjie Yu [République populaire de Chine] ; M Elizabeth Halloran [États-Unis] ; Ira M. Longini [États-Unis] ; Alessandro Vespignani [États-Unis]Source :
- Science (New York, N.Y.) [ 1095-9203 ] ; 2020.
Abstract
Motivated by the rapid spread of COVID-19 in Mainland China, we use a global metapopulation disease transmission model to project the impact of travel limitations on the national and international spread of the epidemic. The model is calibrated based on internationally reported cases, and shows that at the start of the travel ban from Wuhan on 23 January 2020, most Chinese cities had already received many infected travelers. The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in Mainland China, but has a more marked effect at the international scale, where case importations were reduced by nearly 80% until mid February. Modeling results also indicate that sustained 90% travel restrictions to and from Mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.
DOI: 10.1126/science.aba9757
PubMed: 32144116
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<author><name sortKey="Yu, Hongjie" sort="Yu, Hongjie" uniqKey="Yu H" first="Hongjie" last="Yu">Hongjie Yu</name>
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<front><div type="abstract" xml:lang="en">Motivated by the rapid spread of COVID-19 in Mainland China, we use a global metapopulation disease transmission model to project the impact of travel limitations on the national and international spread of the epidemic. The model is calibrated based on internationally reported cases, and shows that at the start of the travel ban from Wuhan on 23 January 2020, most Chinese cities had already received many infected travelers. The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in Mainland China, but has a more marked effect at the international scale, where case importations were reduced by nearly 80% until mid February. Modeling results also indicate that sustained 90% travel restrictions to and from Mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.</div>
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<Abstract><AbstractText>Motivated by the rapid spread of COVID-19 in Mainland China, we use a global metapopulation disease transmission model to project the impact of travel limitations on the national and international spread of the epidemic. The model is calibrated based on internationally reported cases, and shows that at the start of the travel ban from Wuhan on 23 January 2020, most Chinese cities had already received many infected travelers. The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in Mainland China, but has a more marked effect at the international scale, where case importations were reduced by nearly 80% until mid February. Modeling results also indicate that sustained 90% travel restrictions to and from Mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.</AbstractText>
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<Author ValidYN="Y"><LastName>Sun</LastName>
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</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Viboud</LastName>
<ForeName>Cécile</ForeName>
<Initials>C</Initials>
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<AffiliationInfo><Affiliation>Fogarty International Center, NIH, USA.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Xiong</LastName>
<ForeName>Xinyue</ForeName>
<Initials>X</Initials>
<AffiliationInfo><Affiliation>Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Yu</LastName>
<ForeName>Hongjie</ForeName>
<Initials>H</Initials>
<Identifier Source="ORCID">http://orcid.org/0000-0002-6335-5648</Identifier>
<AffiliationInfo><Affiliation>School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.</Affiliation>
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<Author ValidYN="Y"><LastName>Halloran</LastName>
<ForeName>M Elizabeth</ForeName>
<Initials>ME</Initials>
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<AffiliationInfo><Affiliation>Department of Biostatistics, University of Washington, Seattle, WA, USA.</Affiliation>
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<Author ValidYN="Y"><LastName>Longini</LastName>
<ForeName>Ira M</ForeName>
<Initials>IM</Initials>
<Suffix>Jr</Suffix>
<Identifier Source="ORCID">http://orcid.org/0000-0002-2780-9382</Identifier>
<AffiliationInfo><Affiliation>Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA. a.vespignani@northeastern.edu ilongini@ufl.edu.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Vespignani</LastName>
<ForeName>Alessandro</ForeName>
<Initials>A</Initials>
<Identifier Source="ORCID">http://orcid.org/0000-0003-3419-4205</Identifier>
<AffiliationInfo><Affiliation>Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA. a.vespignani@northeastern.edu ilongini@ufl.edu.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>ISI Foundation, Turin, Italy.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2020</Year>
<Month>03</Month>
<Day>06</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>United States</Country>
<MedlineTA>Science</MedlineTA>
<NlmUniqueID>0404511</NlmUniqueID>
<ISSNLinking>0036-8075</ISSNLinking>
</MedlineJournalInfo>
<CitationSubset>IM</CitationSubset>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year>
<Month>01</Month>
<Day>20</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="revised"><Year>2020</Year>
<Month>02</Month>
<Day>07</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted"><Year>2020</Year>
<Month>03</Month>
<Day>05</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez"><Year>2020</Year>
<Month>3</Month>
<Day>8</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed"><Year>2020</Year>
<Month>3</Month>
<Day>8</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline"><Year>2020</Year>
<Month>3</Month>
<Day>8</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>aheadofprint</PublicationStatus>
<ArticleIdList><ArticleId IdType="pubmed">32144116</ArticleId>
<ArticleId IdType="pii">science.aba9757</ArticleId>
<ArticleId IdType="doi">10.1126/science.aba9757</ArticleId>
</ArticleIdList>
</PubmedData>
</pubmed>
</record>
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