Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing.
Identifieur interne : 000418 ( PubMed/Curation ); précédent : 000417; suivant : 000419Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing.
Auteurs : Luca Ferretti [Royaume-Uni] ; Chris Wymant [Royaume-Uni] ; Michelle Kendall [Royaume-Uni] ; Lele Zhao [Royaume-Uni] ; Anel Nurtay [Royaume-Uni] ; Lucie Abeler-Dörner [Royaume-Uni] ; Michael Parker [Royaume-Uni] ; David Bonsall [Royaume-Uni] ; Christophe Fraser [Royaume-Uni]Source :
- Science (New York, N.Y.) [ 1095-9203 ] ; 2020.
Abstract
The newly emergent human virus SARS-CoV-2 is resulting in high fatality rates and incapacitated health systems. Preventing further transmission is a priority. We analyzed key parameters of epidemic spread to estimate the contribution of different transmission routes and determine requirements for case isolation and contact-tracing needed to stop the epidemic. We conclude that viral spread is too fast to be contained by manual contact tracing, but could be controlled if this process was faster, more efficient and happened at scale. A contact-tracing App which builds a memory of proximity contacts and immediately notifies contacts of positive cases can achieve epidemic control if used by enough people. By targeting recommendations to only those at risk, epidemics could be contained without need for mass quarantines ('lock-downs') that are harmful to society. We discuss the ethical requirements for an intervention of this kind.
DOI: 10.1126/science.abb6936
PubMed: 32234805
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Health Information and Discovery, University of Oxford, Oxford, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford</wicri:regionArea></affiliation></author><author><name sortKey="Fraser, Christophe" sort="Fraser, Christophe" uniqKey="Fraser C" first="Christophe" last="Fraser">Christophe Fraser</name><affiliation wicri:level="1"><nlm:affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK. christophe.fraser@bdi.ox.ac.uk.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:32234805</idno><idno 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Oxford, Oxford</wicri:regionArea></affiliation></author><author><name sortKey="Wymant, Chris" sort="Wymant, Chris" uniqKey="Wymant C" first="Chris" last="Wymant">Chris Wymant</name><affiliation wicri:level="1"><nlm:affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford</wicri:regionArea></affiliation></author><author><name sortKey="Kendall, Michelle" sort="Kendall, Michelle" uniqKey="Kendall M" first="Michelle" last="Kendall">Michelle Kendall</name><affiliation wicri:level="1"><nlm:affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford</wicri:regionArea></affiliation></author><author><name sortKey="Zhao, Lele" sort="Zhao, Lele" uniqKey="Zhao L" first="Lele" last="Zhao">Lele Zhao</name><affiliation wicri:level="1"><nlm:affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford</wicri:regionArea></affiliation></author><author><name sortKey="Nurtay, Anel" sort="Nurtay, Anel" uniqKey="Nurtay A" first="Anel" last="Nurtay">Anel Nurtay</name><affiliation wicri:level="1"><nlm:affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford</wicri:regionArea></affiliation></author><author><name sortKey="Abeler Dorner, Lucie" sort="Abeler Dorner, Lucie" uniqKey="Abeler Dorner L" first="Lucie" last="Abeler-Dörner">Lucie Abeler-Dörner</name><affiliation wicri:level="1"><nlm:affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford</wicri:regionArea></affiliation></author><author><name sortKey="Parker, Michael" sort="Parker, Michael" uniqKey="Parker M" first="Michael" last="Parker">Michael Parker</name><affiliation wicri:level="1"><nlm:affiliation>Wellcome Centre for Ethics and the Humanities and Ethox Centre, University of Oxford, Oxford, UK.</nlm:affiliation><country 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UK. christophe.fraser@bdi.ox.ac.uk.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford</wicri:regionArea></affiliation></author></analytic><series><title level="j">Science (New York, N.Y.)</title><idno type="eISSN">1095-9203</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 newly emergent human virus SARS-CoV-2 is resulting in high fatality rates and incapacitated health systems. Preventing further transmission is a priority. We analyzed key parameters of epidemic spread to estimate the contribution of different transmission routes and determine requirements for case isolation and contact-tracing needed to stop the epidemic. We conclude that viral spread is too fast to be contained by manual contact tracing, but could be controlled if this process was faster, more efficient and happened at scale. A contact-tracing App which builds a memory of proximity contacts and immediately notifies contacts of positive cases can achieve epidemic control if used by enough people. By targeting recommendations to only those at risk, epidemics could be contained without need for mass quarantines ('lock-downs') that are harmful to society. We discuss the ethical requirements for an intervention of this kind.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32234805</PMID><DateRevised><Year>2020</Year><Month>04</Month><Day>11</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1095-9203</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2020</Year><Month>Mar</Month><Day>31</Day></PubDate></JournalIssue><Title>Science (New York, N.Y.)</Title><ISOAbbreviation>Science</ISOAbbreviation></Journal><ArticleTitle>Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing.</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">eabb6936</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1126/science.abb6936</ELocationID><Abstract><AbstractText>The newly emergent human virus SARS-CoV-2 is resulting in high fatality rates and incapacitated health systems. Preventing further transmission is a priority. We analyzed key parameters of epidemic spread to estimate the contribution of different transmission routes and determine requirements for case isolation and contact-tracing needed to stop the epidemic. We conclude that viral spread is too fast to be contained by manual contact tracing, but could be controlled if this process was faster, more efficient and happened at scale. A contact-tracing App which builds a memory of proximity contacts and immediately notifies contacts of positive cases can achieve epidemic control if used by enough people. By targeting recommendations to only those at risk, epidemics could be contained without need for mass quarantines ('lock-downs') that are harmful to society. We discuss the ethical requirements for an intervention of this kind.</AbstractText><CopyrightInformation>Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y" EqualContrib="Y"><LastName>Ferretti</LastName><ForeName>Luca</ForeName><Initials>L</Initials><Identifier Source="ORCID">https://orcid.org/0000-0001-7578-7301</Identifier><AffiliationInfo><Affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y" EqualContrib="Y"><LastName>Wymant</LastName><ForeName>Chris</ForeName><Initials>C</Initials><Identifier Source="ORCID">https://orcid.org/0000-0002-9847-8226</Identifier><AffiliationInfo><Affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kendall</LastName><ForeName>Michelle</ForeName><Initials>M</Initials><Identifier Source="ORCID">https://orcid.org/0000-0001-7344-7071</Identifier><AffiliationInfo><Affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhao</LastName><ForeName>Lele</ForeName><Initials>L</Initials><Identifier Source="ORCID">https://orcid.org/0000-0002-2807-1914</Identifier><AffiliationInfo><Affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Nurtay</LastName><ForeName>Anel</ForeName><Initials>A</Initials><Identifier Source="ORCID">https://orcid.org/0000-0001-7107-1656</Identifier><AffiliationInfo><Affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Abeler-Dörner</LastName><ForeName>Lucie</ForeName><Initials>L</Initials><Identifier Source="ORCID">https://orcid.org/0000-0003-3662-4192</Identifier><AffiliationInfo><Affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Parker</LastName><ForeName>Michael</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Wellcome Centre for Ethics and the Humanities and Ethox Centre, University of Oxford, Oxford, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y" EqualContrib="Y"><LastName>Bonsall</LastName><ForeName>David</ForeName><Initials>D</Initials><Identifier Source="ORCID">https://orcid.org/0000-0003-2187-0550</Identifier><AffiliationInfo><Affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Oxford University NHS Trust, University of Oxford, Oxford, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y" EqualContrib="Y"><LastName>Fraser</LastName><ForeName>Christophe</ForeName><Initials>C</Initials><Identifier Source="ORCID">https://orcid.org/0000-0003-2399-9657</Identifier><AffiliationInfo><Affiliation>Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK. christophe.fraser@bdi.ox.ac.uk.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.</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>31</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>03</Month><Day>11</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>03</Month><Day>27</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>4</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>4</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>4</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32234805</ArticleId><ArticleId IdType="pii">science.abb6936</ArticleId><ArticleId IdType="doi">10.1126/science.abb6936</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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