The impact of prior information on estimates of disease transmissibility using Bayesian tools.
Identifieur interne : 000D35 ( PubMed/Checkpoint ); précédent : 000D34; suivant : 000D36The impact of prior information on estimates of disease transmissibility using Bayesian tools.
Auteurs : Carlee B. Moser [États-Unis] ; Mayetri Gupta [États-Unis] ; Brett N. Archer [Afrique du Sud] ; Laura F. White [États-Unis]Source :
- PloS one [ 1932-6203 ] ; 2015.
Descripteurs français
- KwdFr :
- Flambées de maladies (), Grippe humaine (transmission), Grippe humaine (virologie), Grippe humaine (épidémiologie), Hong Kong (épidémiologie), Humains, Intervalles de confiance, République d'Afrique du Sud (épidémiologie), Simulation numérique, Singapour (épidémiologie), Sous-type H1N1 du virus de la grippe A, Syndrome respiratoire aigu sévère (épidémiologie), Théorème de Bayes, Traçage des contacts.
- MESH :
- virologie : Grippe humaine.
- épidémiologie : Grippe humaine, Hong Kong, République d'Afrique du Sud, Singapour, Syndrome respiratoire aigu sévère.
- Flambées de maladies, Humains, Intervalles de confiance, Simulation numérique, Sous-type H1N1 du virus de la grippe A, Théorème de Bayes, Traçage des contacts.
- Wicri :
- geographic : Hong Kong, Singapour, Afrique du Sud.
English descriptors
- KwdEn :
- Bayes Theorem, Computer Simulation, Confidence Intervals, Contact Tracing, Disease Outbreaks (statistics & numerical data), Hong Kong (epidemiology), Humans, Influenza A Virus, H1N1 Subtype, Influenza, Human (epidemiology), Influenza, Human (transmission), Influenza, Human (virology), Severe Acute Respiratory Syndrome (epidemiology), Singapore (epidemiology), South Africa (epidemiology).
- MESH :
- geographic , epidemiology : Hong Kong, Singapore, South Africa.
- epidemiology : Influenza, Human, Severe Acute Respiratory Syndrome.
- statistics & numerical data : Disease Outbreaks.
- transmission : Influenza, Human.
- virology : Influenza, Human.
- Bayes Theorem, Computer Simulation, Confidence Intervals, Contact Tracing, Humans, Influenza A Virus, H1N1 Subtype.
Abstract
The basic reproductive number (R₀) and the distribution of the serial interval (SI) are often used to quantify transmission during an infectious disease outbreak. In this paper, we present estimates of R₀ and SI from the 2003 SARS outbreak in Hong Kong and Singapore, and the 2009 pandemic influenza A(H1N1) outbreak in South Africa using methods that expand upon an existing Bayesian framework. This expanded framework allows for the incorporation of additional information, such as contact tracing or household data, through prior distributions. The results for the R₀ and the SI from the influenza outbreak in South Africa were similar regardless of the prior information (R0 = 1.36-1.46, μ = 2.0-2.7, μ = mean of the SI). The estimates of R₀ and μ for the SARS outbreak ranged from 2.0-4.4 and 7.4-11.3, respectively, and were shown to vary depending on the use of contact tracing data. The impact of the contact tracing data was likely due to the small number of SARS cases relative to the size of the contact tracing sample.
DOI: 10.1371/journal.pone.0118762
PubMed: 25793993
Affiliations:
Links toward previous steps (curation, corpus...)
Links to Exploration step
pubmed:25793993Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">The impact of prior information on estimates of disease transmissibility using Bayesian tools.</title>
<author><name sortKey="Moser, Carlee B" sort="Moser, Carlee B" uniqKey="Moser C" first="Carlee B" last="Moser">Carlee B. Moser</name>
<affiliation wicri:level="2"><nlm:affiliation>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts, United States of America.</nlm:affiliation>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts</wicri:regionArea>
<placeName><region type="state">Massachusetts</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Gupta, Mayetri" sort="Gupta, Mayetri" uniqKey="Gupta M" first="Mayetri" last="Gupta">Mayetri Gupta</name>
<affiliation wicri:level="2"><nlm:affiliation>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts, United States of America.</nlm:affiliation>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts</wicri:regionArea>
<placeName><region type="state">Massachusetts</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Archer, Brett N" sort="Archer, Brett N" uniqKey="Archer B" first="Brett N" last="Archer">Brett N. Archer</name>
<affiliation wicri:level="1"><nlm:affiliation>National Institute for Communicable Diseases, National Health Laboratory Service, Johannesburg, South Africa.</nlm:affiliation>
<country xml:lang="fr">Afrique du Sud</country>
<wicri:regionArea>National Institute for Communicable Diseases, National Health Laboratory Service, Johannesburg</wicri:regionArea>
<wicri:noRegion>Johannesburg</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="White, Laura F" sort="White, Laura F" uniqKey="White L" first="Laura F" last="White">Laura F. White</name>
<affiliation wicri:level="2"><nlm:affiliation>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts, United States of America.</nlm:affiliation>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts</wicri:regionArea>
<placeName><region type="state">Massachusetts</region>
</placeName>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PubMed</idno>
<date when="2015">2015</date>
<idno type="RBID">pubmed:25793993</idno>
<idno type="pmid">25793993</idno>
<idno type="doi">10.1371/journal.pone.0118762</idno>
<idno type="wicri:Area/PubMed/Corpus">000E37</idno>
<idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000E37</idno>
<idno type="wicri:Area/PubMed/Curation">000E37</idno>
<idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000E37</idno>
<idno type="wicri:Area/PubMed/Checkpoint">000D35</idno>
<idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">000D35</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en">The impact of prior information on estimates of disease transmissibility using Bayesian tools.</title>
<author><name sortKey="Moser, Carlee B" sort="Moser, Carlee B" uniqKey="Moser C" first="Carlee B" last="Moser">Carlee B. Moser</name>
<affiliation wicri:level="2"><nlm:affiliation>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts, United States of America.</nlm:affiliation>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts</wicri:regionArea>
<placeName><region type="state">Massachusetts</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Gupta, Mayetri" sort="Gupta, Mayetri" uniqKey="Gupta M" first="Mayetri" last="Gupta">Mayetri Gupta</name>
<affiliation wicri:level="2"><nlm:affiliation>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts, United States of America.</nlm:affiliation>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts</wicri:regionArea>
<placeName><region type="state">Massachusetts</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Archer, Brett N" sort="Archer, Brett N" uniqKey="Archer B" first="Brett N" last="Archer">Brett N. Archer</name>
<affiliation wicri:level="1"><nlm:affiliation>National Institute for Communicable Diseases, National Health Laboratory Service, Johannesburg, South Africa.</nlm:affiliation>
<country xml:lang="fr">Afrique du Sud</country>
<wicri:regionArea>National Institute for Communicable Diseases, National Health Laboratory Service, Johannesburg</wicri:regionArea>
<wicri:noRegion>Johannesburg</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="White, Laura F" sort="White, Laura F" uniqKey="White L" first="Laura F" last="White">Laura F. White</name>
<affiliation wicri:level="2"><nlm:affiliation>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts, United States of America.</nlm:affiliation>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts</wicri:regionArea>
<placeName><region type="state">Massachusetts</region>
</placeName>
</affiliation>
</author>
</analytic>
<series><title level="j">PloS one</title>
<idno type="eISSN">1932-6203</idno>
<imprint><date when="2015" type="published">2015</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Bayes Theorem</term>
<term>Computer Simulation</term>
<term>Confidence Intervals</term>
<term>Contact Tracing</term>
<term>Disease Outbreaks (statistics & numerical data)</term>
<term>Hong Kong (epidemiology)</term>
<term>Humans</term>
<term>Influenza A Virus, H1N1 Subtype</term>
<term>Influenza, Human (epidemiology)</term>
<term>Influenza, Human (transmission)</term>
<term>Influenza, Human (virology)</term>
<term>Severe Acute Respiratory Syndrome (epidemiology)</term>
<term>Singapore (epidemiology)</term>
<term>South Africa (epidemiology)</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr"><term>Flambées de maladies ()</term>
<term>Grippe humaine (transmission)</term>
<term>Grippe humaine (virologie)</term>
<term>Grippe humaine (épidémiologie)</term>
<term>Hong Kong (épidémiologie)</term>
<term>Humains</term>
<term>Intervalles de confiance</term>
<term>République d'Afrique du Sud (épidémiologie)</term>
<term>Simulation numérique</term>
<term>Singapour (épidémiologie)</term>
<term>Sous-type H1N1 du virus de la grippe A</term>
<term>Syndrome respiratoire aigu sévère (épidémiologie)</term>
<term>Théorème de Bayes</term>
<term>Traçage des contacts</term>
</keywords>
<keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Hong Kong</term>
<term>Singapore</term>
<term>South Africa</term>
</keywords>
<keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Influenza, Human</term>
<term>Severe Acute Respiratory Syndrome</term>
</keywords>
<keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Disease Outbreaks</term>
</keywords>
<keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Influenza, Human</term>
</keywords>
<keywords scheme="MESH" qualifier="virologie" xml:lang="fr"><term>Grippe humaine</term>
</keywords>
<keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Influenza, Human</term>
</keywords>
<keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Grippe humaine</term>
<term>Hong Kong</term>
<term>République d'Afrique du Sud</term>
<term>Singapour</term>
<term>Syndrome respiratoire aigu sévère</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Bayes Theorem</term>
<term>Computer Simulation</term>
<term>Confidence Intervals</term>
<term>Contact Tracing</term>
<term>Humans</term>
<term>Influenza A Virus, H1N1 Subtype</term>
</keywords>
<keywords scheme="MESH" xml:lang="fr"><term>Flambées de maladies</term>
<term>Humains</term>
<term>Intervalles de confiance</term>
<term>Simulation numérique</term>
<term>Sous-type H1N1 du virus de la grippe A</term>
<term>Théorème de Bayes</term>
<term>Traçage des contacts</term>
</keywords>
<keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Hong Kong</term>
<term>Singapour</term>
<term>Afrique du Sud</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">The basic reproductive number (R₀) and the distribution of the serial interval (SI) are often used to quantify transmission during an infectious disease outbreak. In this paper, we present estimates of R₀ and SI from the 2003 SARS outbreak in Hong Kong and Singapore, and the 2009 pandemic influenza A(H1N1) outbreak in South Africa using methods that expand upon an existing Bayesian framework. This expanded framework allows for the incorporation of additional information, such as contact tracing or household data, through prior distributions. The results for the R₀ and the SI from the influenza outbreak in South Africa were similar regardless of the prior information (R0 = 1.36-1.46, μ = 2.0-2.7, μ = mean of the SI). The estimates of R₀ and μ for the SARS outbreak ranged from 2.0-4.4 and 7.4-11.3, respectively, and were shown to vary depending on the use of contact tracing data. The impact of the contact tracing data was likely due to the small number of SARS cases relative to the size of the contact tracing sample.</div>
</front>
</TEI>
<pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">25793993</PMID>
<DateCompleted><Year>2015</Year>
<Month>12</Month>
<Day>15</Day>
</DateCompleted>
<DateRevised><Year>2020</Year>
<Month>03</Month>
<Day>06</Day>
</DateRevised>
<Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>10</Volume>
<Issue>3</Issue>
<PubDate><Year>2015</Year>
</PubDate>
</JournalIssue>
<Title>PloS one</Title>
<ISOAbbreviation>PLoS ONE</ISOAbbreviation>
</Journal>
<ArticleTitle>The impact of prior information on estimates of disease transmissibility using Bayesian tools.</ArticleTitle>
<Pagination><MedlinePgn>e0118762</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0118762</ELocationID>
<Abstract><AbstractText>The basic reproductive number (R₀) and the distribution of the serial interval (SI) are often used to quantify transmission during an infectious disease outbreak. In this paper, we present estimates of R₀ and SI from the 2003 SARS outbreak in Hong Kong and Singapore, and the 2009 pandemic influenza A(H1N1) outbreak in South Africa using methods that expand upon an existing Bayesian framework. This expanded framework allows for the incorporation of additional information, such as contact tracing or household data, through prior distributions. The results for the R₀ and the SI from the influenza outbreak in South Africa were similar regardless of the prior information (R0 = 1.36-1.46, μ = 2.0-2.7, μ = mean of the SI). The estimates of R₀ and μ for the SARS outbreak ranged from 2.0-4.4 and 7.4-11.3, respectively, and were shown to vary depending on the use of contact tracing data. The impact of the contact tracing data was likely due to the small number of SARS cases relative to the size of the contact tracing sample.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Moser</LastName>
<ForeName>Carlee B</ForeName>
<Initials>CB</Initials>
<AffiliationInfo><Affiliation>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts, United States of America.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Gupta</LastName>
<ForeName>Mayetri</ForeName>
<Initials>M</Initials>
<AffiliationInfo><Affiliation>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts, United States of America.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Archer</LastName>
<ForeName>Brett N</ForeName>
<Initials>BN</Initials>
<AffiliationInfo><Affiliation>National Institute for Communicable Diseases, National Health Laboratory Service, Johannesburg, South Africa.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>White</LastName>
<ForeName>Laura F</ForeName>
<Initials>LF</Initials>
<AffiliationInfo><Affiliation>Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, Massachusetts, United States of America.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<GrantList CompleteYN="Y"><Grant><GrantID>U54 GM088558</GrantID>
<Acronym>GM</Acronym>
<Agency>NIGMS NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>U54GM088558</GrantID>
<Acronym>GM</Acronym>
<Agency>NIGMS NIH HHS</Agency>
<Country>United States</Country>
</Grant>
</GrantList>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
<PublicationType UI="D052061">Research Support, N.I.H., Extramural</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2015</Year>
<Month>03</Month>
<Day>20</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>United States</Country>
<MedlineTA>PLoS One</MedlineTA>
<NlmUniqueID>101285081</NlmUniqueID>
<ISSNLinking>1932-6203</ISSNLinking>
</MedlineJournalInfo>
<CitationSubset>IM</CitationSubset>
<MeshHeadingList><MeshHeading><DescriptorName UI="D001499" MajorTopicYN="N">Bayes Theorem</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D003198" MajorTopicYN="N">Computer Simulation</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D016001" MajorTopicYN="N">Confidence Intervals</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D016358" MajorTopicYN="N">Contact Tracing</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D004196" MajorTopicYN="N">Disease Outbreaks</DescriptorName>
<QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006723" MajorTopicYN="N" Type="Geographic">Hong Kong</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D053118" MajorTopicYN="N">Influenza A Virus, H1N1 Subtype</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D007251" MajorTopicYN="N">Influenza, Human</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName>
<QualifierName UI="Q000635" MajorTopicYN="Y">transmission</QualifierName>
<QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D045169" MajorTopicYN="N">Severe Acute Respiratory Syndrome</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012846" MajorTopicYN="N" Type="Geographic">Singapore</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D013019" MajorTopicYN="N" Type="Geographic">South Africa</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
</MeshHeadingList>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="received"><Year>2014</Year>
<Month>03</Month>
<Day>27</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted"><Year>2015</Year>
<Month>01</Month>
<Day>22</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez"><Year>2015</Year>
<Month>3</Month>
<Day>21</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed"><Year>2015</Year>
<Month>3</Month>
<Day>21</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline"><Year>2015</Year>
<Month>12</Month>
<Day>17</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>epublish</PublicationStatus>
<ArticleIdList><ArticleId IdType="pubmed">25793993</ArticleId>
<ArticleId IdType="doi">10.1371/journal.pone.0118762</ArticleId>
<ArticleId IdType="pii">PONE-D-14-13446</ArticleId>
<ArticleId IdType="pmc">PMC4368801</ArticleId>
</ArticleIdList>
<ReferenceList><Reference><Citation>Stat Med. 2009 Nov 10;28(25):3049-67</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19630097</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Influenza Other Respir Viruses. 2014 Jan;8(1):33-41</Citation>
<ArticleIdList><ArticleId IdType="pubmed">24209610</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>PLoS Pathog. 2011 Sep;7(9):e1002225</Citation>
<ArticleIdList><ArticleId IdType="pubmed">21909272</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Proc Natl Acad Sci U S A. 2004 Apr 20;101(16):6146-51</Citation>
<ArticleIdList><ArticleId IdType="pubmed">15071187</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Euro Surveill. 2009 Oct 22;14(42):</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19883544</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Epidemiology. 2009 May;20(3):344-7</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19279492</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Stat Med. 2008 Jul 20;27(16):2999-3016</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18058829</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Ann Epidemiol. 2013 Jun;23(6):301-6</Citation>
<ArticleIdList><ArticleId IdType="pubmed">23683708</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Math Biosci. 2008 May;213(1):71-9</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18394654</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Clin Infect Dis. 2011 Jan 1;52 Suppl 1:S123-30</Citation>
<ArticleIdList><ArticleId IdType="pubmed">21342883</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Epidemiology. 2013 Mar;24(2):244-50</Citation>
<ArticleIdList><ArticleId IdType="pubmed">23337238</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Stat Med. 2004 Nov 30;23(22):3469-87</Citation>
<ArticleIdList><ArticleId IdType="pubmed">15505892</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Science. 2003 Jun 20;300(5627):1966-70</Citation>
<ArticleIdList><ArticleId IdType="pubmed">12766207</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Epidemiol Infect. 2014 May;142(5):964-74</Citation>
<ArticleIdList><ArticleId IdType="pubmed">24139316</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>PLoS One. 2013 Aug 30;8(8):e73420</Citation>
<ArticleIdList><ArticleId IdType="pubmed">24023679</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Euro Surveill. 2009 Oct 22;14(42):</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19883549</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Am J Epidemiol. 2004 Sep 15;160(6):509-16</Citation>
<ArticleIdList><ArticleId IdType="pubmed">15353409</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Am J Epidemiol. 2012 Aug 1;176(3):196-203</Citation>
<ArticleIdList><ArticleId IdType="pubmed">22791742</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Euro Surveill. 2010 Jul 01;15(26):</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20619130</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>PLoS One. 2012;7(11):e49482</Citation>
<ArticleIdList><ArticleId IdType="pubmed">23166682</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>J Infect Dis. 2012 Dec 15;206 Suppl 1:S148-53</Citation>
<ArticleIdList><ArticleId IdType="pubmed">23169962</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>BMC Med. 2013 Oct 02;11:214</Citation>
<ArticleIdList><ArticleId IdType="pubmed">24083506</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Influenza Other Respir Viruses. 2009 Nov;3(6):267-76</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19903209</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Math Biosci. 2007 Jul;208(1):300-11</Citation>
<ArticleIdList><ArticleId IdType="pubmed">17174352</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Biostatistics. 2011 Apr;12(2):303-12</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20858771</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
</PubmedData>
</pubmed>
<affiliations><list><country><li>Afrique du Sud</li>
<li>États-Unis</li>
</country>
<region><li>Massachusetts</li>
</region>
</list>
<tree><country name="États-Unis"><region name="Massachusetts"><name sortKey="Moser, Carlee B" sort="Moser, Carlee B" uniqKey="Moser C" first="Carlee B" last="Moser">Carlee B. Moser</name>
</region>
<name sortKey="Gupta, Mayetri" sort="Gupta, Mayetri" uniqKey="Gupta M" first="Mayetri" last="Gupta">Mayetri Gupta</name>
<name sortKey="White, Laura F" sort="White, Laura F" uniqKey="White L" first="Laura F" last="White">Laura F. White</name>
</country>
<country name="Afrique du Sud"><noRegion><name sortKey="Archer, Brett N" sort="Archer, Brett N" uniqKey="Archer B" first="Brett N" last="Archer">Brett N. Archer</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Sante/explor/SrasV1/Data/PubMed/Checkpoint
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000D35 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/PubMed/Checkpoint/biblio.hfd -nk 000D35 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Sante |area= SrasV1 |flux= PubMed |étape= Checkpoint |type= RBID |clé= pubmed:25793993 |texte= The impact of prior information on estimates of disease transmissibility using Bayesian tools. }}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/PubMed/Checkpoint/RBID.i -Sk "pubmed:25793993" \ | HfdSelect -Kh $EXPLOR_AREA/Data/PubMed/Checkpoint/biblio.hfd \ | NlmPubMed2Wicri -a SrasV1
![]() | This area was generated with Dilib version V0.6.33. | ![]() |