Bayesian Reconstruction of Disease Outbreaks by Combining Epidemiologic and Genomic Data
Identifieur interne : 001697 ( Main/Exploration ); précédent : 001696; suivant : 001698Bayesian Reconstruction of Disease Outbreaks by Combining Epidemiologic and Genomic Data
Auteurs : Thibaut Jombart ; Anne Cori ; Xavier Didelot ; Simon Cauchemez ; Christophe Fraser ; Neil FergusonSource :
- PLoS Computational Biology [ 1553-734X ] ; 2014.
Descripteurs français
- KwdFr :
- Algorithmes, Contrôle des maladies contagieuses, Entropie, Flambées de maladies, Génome viral, Génomique, Humains, Langages de programmation, Logiciel, Mutation, Probabilité, Simulation numérique, Singapour, Syndrome respiratoire aigu sévère (virologie), Syndrome respiratoire aigu sévère (épidémiologie), Théorème de Bayes, Virus du SRAS (génétique), Épidémies.
- MESH :
- génétique : Virus du SRAS.
- virologie : Syndrome respiratoire aigu sévère.
- épidémiologie : Syndrome respiratoire aigu sévère.
- Algorithmes, Contrôle des maladies contagieuses, Entropie, Flambées de maladies, Génome viral, Génomique, Humains, Langages de programmation, Logiciel, Mutation, Probabilité, Simulation numérique, Singapour, Théorème de Bayes, Épidémies.
- Wicri :
- geographic : Singapour.
English descriptors
- KwdEn :
- Algorithms, Bayes Theorem, Communicable Disease Control, Computer Simulation, Disease Outbreaks, Entropy, Epidemics, Genome, Viral, Genomics, Humans, Mutation, Probability, Programming Languages, SARS Virus (genetics), Severe Acute Respiratory Syndrome (epidemiology), Severe Acute Respiratory Syndrome (virology), Singapore, Software.
- MESH :
- geographic : Singapore.
- epidemiology : Severe Acute Respiratory Syndrome.
- genetics : SARS Virus.
- virology : Severe Acute Respiratory Syndrome.
- Algorithms, Bayes Theorem, Communicable Disease Control, Computer Simulation, Disease Outbreaks, Entropy, Epidemics, Genome, Viral, Genomics, Humans, Mutation, Probability, Programming Languages, Software.
Abstract
Recent years have seen progress in the development of statistically rigorous frameworks to infer outbreak transmission trees (“who infected whom”) from epidemiological and genetic data. Making use of pathogen genome sequences in such analyses remains a challenge, however, with a variety of heuristic approaches having been explored to date. We introduce a statistical method exploiting both pathogen sequences and collection dates to unravel the dynamics of densely sampled outbreaks. Our approach identifies likely transmission events and infers dates of infections, unobserved cases and separate introductions of the disease. It also proves useful for inferring numbers of secondary infections and identifying heterogeneous infectivity and super-spreaders. After testing our approach using simulations, we illustrate the method with the analysis of the beginning of the 2003 Singaporean outbreak of Severe Acute Respiratory Syndrome (SARS), providing new insights into the early stage of this epidemic. Our approach is the first tool for disease outbreak reconstruction from genetic data widely available as free software, the R package
Url:
DOI: 10.1371/journal.pcbi.1003457
PubMed: 24465202
PubMed Central: 3900386
Affiliations:
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Le document en format XML
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id="aff1"></nlm:aff></affiliation></author><author><name sortKey="Fraser, Christophe" sort="Fraser, Christophe" uniqKey="Fraser C" first="Christophe" last="Fraser">Christophe Fraser</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author><author><name sortKey="Ferguson, Neil" sort="Ferguson, Neil" uniqKey="Ferguson N" first="Neil" last="Ferguson">Neil Ferguson</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author></analytic><series><title level="j">PLoS Computational Biology</title><idno type="ISSN">1553-734X</idno><idno type="eISSN">1553-7358</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Bayes Theorem</term><term>Communicable Disease Control</term><term>Computer Simulation</term><term>Disease Outbreaks</term><term>Entropy</term><term>Epidemics</term><term>Genome, Viral</term><term>Genomics</term><term>Humans</term><term>Mutation</term><term>Probability</term><term>Programming Languages</term><term>SARS Virus (genetics)</term><term>Severe Acute Respiratory Syndrome (epidemiology)</term><term>Severe Acute Respiratory Syndrome (virology)</term><term>Singapore</term><term>Software</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term><term>Contrôle des maladies contagieuses</term><term>Entropie</term><term>Flambées de maladies</term><term>Génome viral</term><term>Génomique</term><term>Humains</term><term>Langages de programmation</term><term>Logiciel</term><term>Mutation</term><term>Probabilité</term><term>Simulation numérique</term><term>Singapour</term><term>Syndrome respiratoire aigu sévère (virologie)</term><term>Syndrome respiratoire aigu sévère (épidémiologie)</term><term>Théorème de Bayes</term><term>Virus du SRAS (génétique)</term><term>Épidémies</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>Singapore</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Severe Acute Respiratory Syndrome</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>SARS Virus</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Virus du SRAS</term></keywords><keywords scheme="MESH" qualifier="virologie" xml:lang="fr"><term>Syndrome respiratoire aigu sévère</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Severe Acute Respiratory Syndrome</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Syndrome respiratoire aigu sévère</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Bayes Theorem</term><term>Communicable Disease Control</term><term>Computer Simulation</term><term>Disease Outbreaks</term><term>Entropy</term><term>Epidemics</term><term>Genome, Viral</term><term>Genomics</term><term>Humans</term><term>Mutation</term><term>Probability</term><term>Programming Languages</term><term>Software</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Contrôle des maladies contagieuses</term><term>Entropie</term><term>Flambées de maladies</term><term>Génome viral</term><term>Génomique</term><term>Humains</term><term>Langages de programmation</term><term>Logiciel</term><term>Mutation</term><term>Probabilité</term><term>Simulation numérique</term><term>Singapour</term><term>Théorème de Bayes</term><term>Épidémies</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Singapour</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Recent years have seen progress in the development of statistically rigorous frameworks to infer outbreak transmission trees (“who infected whom”) from epidemiological and genetic data. Making use of pathogen genome sequences in such analyses remains a challenge, however, with a variety of heuristic approaches having been explored to date. We introduce a statistical method exploiting both pathogen sequences and collection dates to unravel the dynamics of densely sampled outbreaks. Our approach identifies likely transmission events and infers dates of infections, unobserved cases and separate introductions of the disease. It also proves useful for inferring numbers of secondary infections and identifying heterogeneous infectivity and super-spreaders. After testing our approach using simulations, we illustrate the method with the analysis of the beginning of the 2003 Singaporean outbreak of Severe Acute Respiratory Syndrome (SARS), providing new insights into the early stage of this epidemic. Our approach is the first tool for disease outbreak reconstruction from genetic data widely available as free software, the R package <italic>outbreaker</italic>. It is applicable to various densely sampled epidemics, and improves previous approaches by detecting unobserved and imported cases, as well as allowing multiple introductions of the pathogen. Because of its generality, we believe this method will become a tool of choice for the analysis of densely sampled disease outbreaks, and will form a rigorous framework for subsequent methodological developments.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Haydon, Dt" uniqKey="Haydon D">DT Haydon</name></author><author><name sortKey="Chase Topping, M" uniqKey="Chase Topping M">M Chase-Topping</name></author><author><name sortKey="Shaw, Dj" uniqKey="Shaw D">DJ Shaw</name></author><author><name sortKey="Matthews, L" uniqKey="Matthews L">L Matthews</name></author><author><name sortKey="Friar, Jk" uniqKey="Friar J">JK Friar</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Cauchemez, S" uniqKey="Cauchemez S">S Cauchemez</name></author><author><name sortKey="Boelle, Py" uniqKey="Boelle P">PY Boelle</name></author><author><name sortKey="Donnelly, Ca" uniqKey="Donnelly C">CA 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uniqKey="Koopman J">JS Koopman</name></author><author><name sortKey="Ward, Mj" uniqKey="Ward M">MJ Ward</name></author><author><name sortKey="Brown, Al" uniqKey="Brown A">AL Brown</name></author><author><name sortKey="Frost, Sd" uniqKey="Frost S">SD Frost</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Rasmussen, Da" uniqKey="Rasmussen D">DA Rasmussen</name></author><author><name sortKey="Ratmann, O" uniqKey="Ratmann O">O Ratmann</name></author><author><name sortKey="Koelle, K" uniqKey="Koelle K">K Koelle</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Young, Bc" uniqKey="Young B">BC Young</name></author><author><name sortKey="Golubchik, T" uniqKey="Golubchik T">T Golubchik</name></author><author><name sortKey="Batty, Em" uniqKey="Batty E">EM Batty</name></author><author><name sortKey="Fung, R" uniqKey="Fung R">R Fung</name></author><author><name sortKey="Larner Svensson, H" uniqKey="Larner Svensson H">H 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sortKey="Harris, Sr" uniqKey="Harris S">SR Harris</name></author><author><name sortKey="Cartwright, Ej" uniqKey="Cartwright E">EJ Cartwright</name></author><author><name sortKey="Torok, Me" uniqKey="Torok M">ME Torok</name></author><author><name sortKey="Holden, Mt" uniqKey="Holden M">MT Holden</name></author><author><name sortKey="Brown, Nm" uniqKey="Brown N">NM Brown</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Varin, C" uniqKey="Varin C">C Varin</name></author><author><name sortKey="Reid, N" uniqKey="Reid N">N Reid</name></author><author><name sortKey="Firth, D" uniqKey="Firth D">D Firth</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hens, N" uniqKey="Hens N">N Hens</name></author><author><name sortKey="Calatayud, L" uniqKey="Calatayud L">L Calatayud</name></author><author><name sortKey="Kurkela, S" uniqKey="Kurkela S">S Kurkela</name></author><author><name sortKey="Tamme, T" uniqKey="Tamme T">T Tamme</name></author><author><name sortKey="Wallinga, J" uniqKey="Wallinga J">J Wallinga</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Edgar, Rc" uniqKey="Edgar R">RC Edgar</name></author></analytic></biblStruct></listBibl></div1></back></TEI><affiliations><list></list><tree><noCountry><name sortKey="Cauchemez, Simon" sort="Cauchemez, Simon" uniqKey="Cauchemez S" first="Simon" last="Cauchemez">Simon Cauchemez</name><name sortKey="Cori, Anne" sort="Cori, Anne" uniqKey="Cori A" first="Anne" last="Cori">Anne Cori</name><name sortKey="Didelot, Xavier" sort="Didelot, Xavier" uniqKey="Didelot X" first="Xavier" last="Didelot">Xavier Didelot</name><name sortKey="Ferguson, Neil" sort="Ferguson, Neil" uniqKey="Ferguson N" first="Neil" last="Ferguson">Neil Ferguson</name><name sortKey="Fraser, Christophe" sort="Fraser, Christophe" uniqKey="Fraser C" first="Christophe" last="Fraser">Christophe Fraser</name><name sortKey="Jombart, Thibaut" sort="Jombart, Thibaut" uniqKey="Jombart T" first="Thibaut" last="Jombart">Thibaut Jombart</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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