Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak.
Identifieur interne : 000017 ( PubMed/Curation ); précédent : 000016; suivant : 000018Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak.
Auteurs : Chad R. Wells [États-Unis] ; Pratha Sah [États-Unis] ; Seyed M. Moghadas [Canada] ; Abhishek Pandey [États-Unis] ; Affan Shoukat [États-Unis] ; Yaning Wang [République populaire de Chine] ; Zheng Wang [États-Unis] ; Lauren A. Meyers [États-Unis] ; Burton H. Singer [États-Unis] ; Alison P. Galvani [États-Unis]Source :
- Proceedings of the National Academy of Sciences of the United States of America [ 1091-6490 ] ; 2020.
Abstract
The novel coronavirus outbreak (COVID-19) in mainland China has rapidly spread across the globe. Within 2 mo since the outbreak was first reported on December 31, 2019, a total of 566 Severe Acute Respiratory Syndrome (SARS CoV-2) cases have been confirmed in 26 other countries. Travel restrictions and border control measures have been enforced in China and other countries to limit the spread of the outbreak. We estimate the impact of these control measures and investigate the role of the airport travel network on the global spread of the COVID-19 outbreak. Our results show that the daily risk of exporting at least a single SARS CoV-2 case from mainland China via international travel exceeded 95% on January 13, 2020. We found that 779 cases (95% CI: 632 to 967) would have been exported by February 15, 2020 without any border or travel restrictions and that the travel lockdowns enforced by the Chinese government averted 70.5% (95% CI: 68.8 to 72.0%) of these cases. In addition, during the first three and a half weeks of implementation, the travel restrictions decreased the daily rate of exportation by 81.3% (95% CI: 80.5 to 82.1%), on average. At this early stage of the epidemic, reduction in the rate of exportation could delay the importation of cases into cities unaffected by the COVID-19 outbreak, buying time to coordinate an appropriate public health response.
DOI: 10.1073/pnas.2002616117
PubMed: 32170017
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Wells</name><affiliation wicri:level="2"><nlm:affiliation>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">Connecticut</region></placeName><wicri:cityArea>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven</wicri:cityArea></affiliation></author><author><name sortKey="Sah, Pratha" sort="Sah, Pratha" uniqKey="Sah P" first="Pratha" last="Sah">Pratha Sah</name><affiliation wicri:level="2"><nlm:affiliation>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">Connecticut</region></placeName><wicri:cityArea>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven</wicri:cityArea></affiliation></author><author><name sortKey="Moghadas, Seyed M" sort="Moghadas, Seyed M" uniqKey="Moghadas S" first="Seyed M" last="Moghadas">Seyed M. Moghadas</name><affiliation wicri:level="1"><nlm:affiliation>Agent-Based Modelling Laboratory, York University, Toronto, ON M3J 1P3, Canada.</nlm:affiliation><country xml:lang="fr">Canada</country><wicri:regionArea>Agent-Based Modelling Laboratory, York University, Toronto, ON M3J 1P3</wicri:regionArea></affiliation></author><author><name sortKey="Pandey, Abhishek" sort="Pandey, Abhishek" uniqKey="Pandey A" first="Abhishek" last="Pandey">Abhishek Pandey</name><affiliation wicri:level="2"><nlm:affiliation>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">Connecticut</region></placeName><wicri:cityArea>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven</wicri:cityArea></affiliation></author><author><name sortKey="Shoukat, Affan" sort="Shoukat, Affan" uniqKey="Shoukat A" first="Affan" last="Shoukat">Affan Shoukat</name><affiliation wicri:level="2"><nlm:affiliation>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">Connecticut</region></placeName><wicri:cityArea>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven</wicri:cityArea></affiliation></author><author><name sortKey="Wang, Yaning" sort="Wang, Yaning" uniqKey="Wang Y" first="Yaning" last="Wang">Yaning Wang</name><affiliation wicri:level="1"><nlm:affiliation>State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, 100101 Beijing, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, 100101 Beijing</wicri:regionArea></affiliation></author><author><name sortKey="Wang, Zheng" sort="Wang, Zheng" uniqKey="Wang Z" first="Zheng" last="Wang">Zheng Wang</name><affiliation wicri:level="2"><nlm:affiliation>Department of Biostatistics, Yale School of Public Health, New Haven, CT 06510.</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">Connecticut</region></placeName><wicri:cityArea>Department of Biostatistics, Yale School of Public Health, New Haven</wicri:cityArea></affiliation></author><author><name sortKey="Meyers, Lauren A" sort="Meyers, Lauren A" uniqKey="Meyers L" first="Lauren A" last="Meyers">Lauren A. Meyers</name><affiliation wicri:level="2"><nlm:affiliation>Department of Integrative Biology, The University of Texas at Austin, Austin, TX 78712.</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">Texas</region></placeName><wicri:cityArea>Department of Integrative Biology, The University of Texas at Austin, Austin</wicri:cityArea></affiliation></author><author><name sortKey="Singer, Burton H" sort="Singer, Burton H" uniqKey="Singer B" first="Burton H" last="Singer">Burton H. Singer</name><affiliation wicri:level="1"><nlm:affiliation>Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610 bhsinger@epi.ufl.edu.</nlm:affiliation><country wicri:rule="url">États-Unis</country><wicri:regionArea>Emerging Pathogens Institute, University of Florida, Gainesville</wicri:regionArea></affiliation></author><author><name sortKey="Galvani, Alison P" sort="Galvani, Alison P" uniqKey="Galvani A" first="Alison P" last="Galvani">Alison P. Galvani</name><affiliation wicri:level="2"><nlm:affiliation>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">Connecticut</region></placeName><wicri:cityArea>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven</wicri:cityArea></affiliation></author></analytic><series><title level="j">Proceedings of the National Academy of Sciences of the United States of America</title><idno type="eISSN">1091-6490</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">The novel coronavirus outbreak (COVID-19) in mainland China has rapidly spread across the globe. Within 2 mo since the outbreak was first reported on December 31, 2019, a total of 566 Severe Acute Respiratory Syndrome (SARS CoV-2) cases have been confirmed in 26 other countries. Travel restrictions and border control measures have been enforced in China and other countries to limit the spread of the outbreak. We estimate the impact of these control measures and investigate the role of the airport travel network on the global spread of the COVID-19 outbreak. Our results show that the daily risk of exporting at least a single SARS CoV-2 case from mainland China via international travel exceeded 95% on January 13, 2020. We found that 779 cases (95% CI: 632 to 967) would have been exported by February 15, 2020 without any border or travel restrictions and that the travel lockdowns enforced by the Chinese government averted 70.5% (95% CI: 68.8 to 72.0%) of these cases. In addition, during the first three and a half weeks of implementation, the travel restrictions decreased the daily rate of exportation by 81.3% (95% CI: 80.5 to 82.1%), on average. At this early stage of the epidemic, reduction in the rate of exportation could delay the importation of cases into cities unaffected by the COVID-19 outbreak, buying time to coordinate an appropriate public health response.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32170017</PMID><DateRevised><Year>2020</Year><Month>03</Month><Day>14</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1091-6490</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2020</Year><Month>Mar</Month><Day>13</Day></PubDate></JournalIssue><Title>Proceedings of the National Academy of Sciences of the United States of America</Title><ISOAbbreviation>Proc. Natl. Acad. Sci. U.S.A.</ISOAbbreviation></Journal><ArticleTitle>Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak.</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">202002616</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1073/pnas.2002616117</ELocationID><Abstract><AbstractText>The novel coronavirus outbreak (COVID-19) in mainland China has rapidly spread across the globe. Within 2 mo since the outbreak was first reported on December 31, 2019, a total of 566 Severe Acute Respiratory Syndrome (SARS CoV-2) cases have been confirmed in 26 other countries. Travel restrictions and border control measures have been enforced in China and other countries to limit the spread of the outbreak. We estimate the impact of these control measures and investigate the role of the airport travel network on the global spread of the COVID-19 outbreak. Our results show that the daily risk of exporting at least a single SARS CoV-2 case from mainland China via international travel exceeded 95% on January 13, 2020. We found that 779 cases (95% CI: 632 to 967) would have been exported by February 15, 2020 without any border or travel restrictions and that the travel lockdowns enforced by the Chinese government averted 70.5% (95% CI: 68.8 to 72.0%) of these cases. In addition, during the first three and a half weeks of implementation, the travel restrictions decreased the daily rate of exportation by 81.3% (95% CI: 80.5 to 82.1%), on average. At this early stage of the epidemic, reduction in the rate of exportation could delay the importation of cases into cities unaffected by the COVID-19 outbreak, buying time to coordinate an appropriate public health response.</AbstractText><CopyrightInformation>Copyright © 2020 the Author(s). Published by PNAS.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Wells</LastName><ForeName>Chad R</ForeName><Initials>CR</Initials><Identifier Source="ORCID">http://orcid.org/0000-0003-1370-8350</Identifier><AffiliationInfo><Affiliation>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Sah</LastName><ForeName>Pratha</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Moghadas</LastName><ForeName>Seyed M</ForeName><Initials>SM</Initials><AffiliationInfo><Affiliation>Agent-Based Modelling Laboratory, York University, Toronto, ON M3J 1P3, Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Pandey</LastName><ForeName>Abhishek</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Shoukat</LastName><ForeName>Affan</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Yaning</ForeName><Initials>Y</Initials><Identifier Source="ORCID">http://orcid.org/0000-0001-8982-5604</Identifier><AffiliationInfo><Affiliation>State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, 100101 Beijing, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Zheng</ForeName><Initials>Z</Initials><Identifier Source="ORCID">http://orcid.org/0000-0002-8849-8549</Identifier><AffiliationInfo><Affiliation>Department of Biostatistics, Yale School of Public Health, New Haven, CT 06510.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Meyers</LastName><ForeName>Lauren A</ForeName><Initials>LA</Initials><AffiliationInfo><Affiliation>Department of Integrative Biology, The University of Texas at Austin, Austin, TX 78712.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Santa Fe Institute, Santa Fe, NM 87501.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Singer</LastName><ForeName>Burton H</ForeName><Initials>BH</Initials><AffiliationInfo><Affiliation>Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610 bhsinger@epi.ufl.edu.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Galvani</LastName><ForeName>Alison P</ForeName><Initials>AP</Initials><AffiliationInfo><Affiliation>Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.</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>13</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Proc Natl Acad Sci U S A</MedlineTA><NlmUniqueID>7505876</NlmUniqueID><ISSNLinking>0027-8424</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">COVID-19</Keyword><Keyword MajorTopicYN="N">SARS-CoV-2</Keyword><Keyword MajorTopicYN="N">disease importation</Keyword><Keyword MajorTopicYN="N">screening</Keyword><Keyword MajorTopicYN="N">surveillance</Keyword></KeywordList><CoiStatement>The authors declare no competing interest.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>3</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>3</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>3</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32170017</ArticleId><ArticleId IdType="pii">2002616117</ArticleId><ArticleId IdType="doi">10.1073/pnas.2002616117</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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