Epidemic contact tracing via communication traces.
Identifieur interne : 003690 ( PubMed/Curation ); précédent : 003689; suivant : 003691Epidemic contact tracing via communication traces.
Auteurs : Katayoun Farrahi [Royaume-Uni] ; Rémi Emonet [France] ; Manuel Cebrian [Australie]Source :
- PloS one [ 1932-6203 ] ; 2014.
Descripteurs français
- KwdFr :
- MESH :
- épidémiologie : Maladies transmissibles.
- Communication, Femelle, Humains, Modèles théoriques, Mâle, Traçage des contacts, Épidémies.
English descriptors
- KwdEn :
- MESH :
- epidemiology : Communicable Diseases.
- transmission : Communicable Diseases.
- Communication, Contact Tracing, Epidemics, Female, Humans, Male, Models, Theoretical.
Abstract
Traditional contact tracing relies on knowledge of the interpersonal network of physical interactions, where contagious outbreaks propagate. However, due to privacy constraints and noisy data assimilation, this network is generally difficult to reconstruct accurately. Communication traces obtained by mobile phones are known to be good proxies for the physical interaction network, and they may provide a valuable tool for contact tracing. Motivated by this assumption, we propose a model for contact tracing, where an infection is spreading in the physical interpersonal network, which can never be fully recovered; and contact tracing is occurring in a communication network which acts as a proxy for the first. We apply this dual model to a dataset covering 72 students over a 9 month period, for which both the physical interactions as well as the mobile communication traces are known. Our results suggest that a wide range of contact tracing strategies may significantly reduce the final size of the epidemic, by mainly affecting its peak of incidence. However, we find that for low overlap between the face-to-face and communication interaction network, contact tracing is only efficient at the beginning of the outbreak, due to rapidly increasing costs as the epidemic evolves. Overall, contact tracing via mobile phone communication traces may be a viable option to arrest contagious outbreaks.
DOI: 10.1371/journal.pone.0095133
PubMed: 24787614
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Department of Computer Science and Engineering, University of California at San Diego, La Jolla, California, United States of America; National Information and Communications Technology Australia, Melbourne, Victoria, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Media Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America; Department of Computer Science and Engineering, University of California at San Diego, La Jolla, California, United States of America; National Information and Communications Technology Australia, Melbourne, Victoria</wicri:regionArea></affiliation></author></analytic><series><title level="j">PloS one</title><idno type="eISSN">1932-6203</idno><imprint><date when="2014" type="published">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Communicable Diseases (epidemiology)</term><term>Communicable Diseases (transmission)</term><term>Communication</term><term>Contact Tracing</term><term>Epidemics</term><term>Female</term><term>Humans</term><term>Male</term><term>Models, Theoretical</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Communication</term><term>Femelle</term><term>Humains</term><term>Maladies transmissibles (transmission)</term><term>Maladies transmissibles (épidémiologie)</term><term>Modèles théoriques</term><term>Mâle</term><term>Traçage des contacts</term><term>Épidémies</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Communicable Diseases</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Communicable Diseases</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Maladies transmissibles</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Communication</term><term>Contact Tracing</term><term>Epidemics</term><term>Female</term><term>Humans</term><term>Male</term><term>Models, Theoretical</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Communication</term><term>Femelle</term><term>Humains</term><term>Modèles théoriques</term><term>Mâle</term><term>Traçage des contacts</term><term>Épidémies</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Traditional contact tracing relies on knowledge of the interpersonal network of physical interactions, where contagious outbreaks propagate. However, due to privacy constraints and noisy data assimilation, this network is generally difficult to reconstruct accurately. Communication traces obtained by mobile phones are known to be good proxies for the physical interaction network, and they may provide a valuable tool for contact tracing. Motivated by this assumption, we propose a model for contact tracing, where an infection is spreading in the physical interpersonal network, which can never be fully recovered; and contact tracing is occurring in a communication network which acts as a proxy for the first. We apply this dual model to a dataset covering 72 students over a 9 month period, for which both the physical interactions as well as the mobile communication traces are known. Our results suggest that a wide range of contact tracing strategies may significantly reduce the final size of the epidemic, by mainly affecting its peak of incidence. However, we find that for low overlap between the face-to-face and communication interaction network, contact tracing is only efficient at the beginning of the outbreak, due to rapidly increasing costs as the epidemic evolves. Overall, contact tracing via mobile phone communication traces may be a viable option to arrest contagious outbreaks.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">24787614</PMID><DateCreated><Year>2014</Year><Month>05</Month><Day>05</Day></DateCreated><DateCompleted><Year>2014</Year><Month>12</Month><Day>18</Day></DateCompleted><DateRevised><Year>2017</Year><Month>02</Month><Day>20</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN><JournalIssue CitedMedium="Internet"><Volume>9</Volume><Issue>5</Issue><PubDate><Year>2014</Year></PubDate></JournalIssue><Title>PloS one</Title><ISOAbbreviation>PLoS ONE</ISOAbbreviation></Journal><ArticleTitle>Epidemic contact tracing via communication traces.</ArticleTitle><Pagination><MedlinePgn>e95133</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0095133</ELocationID><Abstract><AbstractText>Traditional contact tracing relies on knowledge of the interpersonal network of physical interactions, where contagious outbreaks propagate. However, due to privacy constraints and noisy data assimilation, this network is generally difficult to reconstruct accurately. Communication traces obtained by mobile phones are known to be good proxies for the physical interaction network, and they may provide a valuable tool for contact tracing. Motivated by this assumption, we propose a model for contact tracing, where an infection is spreading in the physical interpersonal network, which can never be fully recovered; and contact tracing is occurring in a communication network which acts as a proxy for the first. We apply this dual model to a dataset covering 72 students over a 9 month period, for which both the physical interactions as well as the mobile communication traces are known. Our results suggest that a wide range of contact tracing strategies may significantly reduce the final size of the epidemic, by mainly affecting its peak of incidence. However, we find that for low overlap between the face-to-face and communication interaction network, contact tracing is only efficient at the beginning of the outbreak, due to rapidly increasing costs as the epidemic evolves. Overall, contact tracing via mobile phone communication traces may be a viable option to arrest contagious outbreaks.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Farrahi</LastName><ForeName>Katayoun</ForeName><Initials>K</Initials><AffiliationInfo><Affiliation>Department of Computing, Goldsmiths, University of London, London, United Kingdom.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Emonet</LastName><ForeName>Rémi</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Department of Machine Learning, Laboratoire Hubert Curien, Saint-Etienne, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Cebrian</LastName><ForeName>Manuel</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Media Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America; Department of Computer Science and Engineering, University of California at San Diego, La Jolla, California, United States of America; National Information and Communications Technology Australia, Melbourne, Victoria, Australia.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2014</Year><Month>05</Month><Day>01</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS One</MedlineTA><NlmUniqueID>101285081</NlmUniqueID><ISSNLinking>1932-6203</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>PLoS One. 2011;6(2):e17144</RefSource><PMID Version="1">21386902</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Proc Natl Acad Sci U S A. 2009 Dec 22;106(51):21484-9</RefSource><PMID Version="1">20018697</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Proc Biol Sci. 2003 Dec 22;270(1533):2565-71</RefSource><PMID Version="1">14728778</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Proc Natl Acad Sci U S A. 2010 Dec 21;107(51):22020-5</RefSource><PMID Version="1">21149721</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Proc Natl Acad Sci U S A. 2010 Dec 28;107(52):22436-41</RefSource><PMID Version="1">21148099</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>PLoS One. 2013;8(1):e52168</RefSource><PMID Version="1">23300964</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Proc Natl Acad Sci U S A. 2009 Sep 8;106(36):15274-8</RefSource><PMID Version="1">19706491</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>PLoS Comput Biol. 2010 Apr;6(4):e1000736</RefSource><PMID Version="1">20386735</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>J Comput Sci. 2010 Aug 1;1(3):132-145</RefSource><PMID Version="1">21415939</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>N Engl J Med. 2013 Aug 1;369(5):401-4</RefSource><PMID Version="1">23822655</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>PLoS Comput Biol. 2012;8(7):e1002616</RefSource><PMID Version="1">22844241</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Science. 2012 Oct 12;338(6104):267-70</RefSource><PMID Version="1">23066082</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>BMC Med. 2011;9:87</RefSource><PMID Version="1">21771290</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Nat Phys. 2011 Jul 1;7:581-586</RefSource><PMID Version="1">21799702</PMID></CommentsCorrections></CommentsCorrectionsList><MeshHeadingList><MeshHeading><DescriptorName UI="D003141" MajorTopicYN="N">Communicable Diseases</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000635" MajorTopicYN="Y">transmission</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D003142" MajorTopicYN="N">Communication</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D016358" MajorTopicYN="Y">Contact Tracing</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058872" MajorTopicYN="Y">Epidemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008962" MajorTopicYN="Y">Models, Theoretical</DescriptorName></MeshHeading></MeshHeadingList><OtherID Source="NLM">PMC4006791</OtherID></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2013</Year><Month>07</Month><Day>10</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2014</Year><Month>03</Month><Day>24</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2014</Year><Month>5</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2014</Year><Month>5</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2014</Year><Month>12</Month><Day>19</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">24787614</ArticleId><ArticleId IdType="doi">10.1371/journal.pone.0095133</ArticleId><ArticleId IdType="pii">PONE-D-13-30076</ArticleId><ArticleId IdType="pmc">PMC4006791</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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