Bayesian Markov switching models for the early detection of influenza epidemics.
Identifieur interne : 000550 ( Main/Exploration ); précédent : 000549; suivant : 000551Bayesian Markov switching models for the early detection of influenza epidemics.
Auteurs : Miguel A. Martínez-Beneito [Espagne] ; David Conesa ; Antonio L Pez-Quílez ; Aurora L Pez-MasideSource :
- Statistics in medicine [ 0277-6715 ] ; 2008.
Descripteurs français
- KwdFr :
- MESH :
- Wicri :
- geographic : Espagne.
English descriptors
- KwdEn :
- MESH :
- geographic , epidemiology : Spain.
- epidemiology : Influenza, Human.
- Bayes Theorem, Disease Outbreaks, Humans, Incidence, Markov Chains, Models, Statistical, Regression Analysis, Sentinel Surveillance, Space-Time Clustering.
Abstract
The early detection of outbreaks of diseases is one of the most challenging objectives of epidemiological surveillance systems. In this paper, a Markov switching model is introduced to determine the epidemic and non-epidemic periods from influenza surveillance data: the process of differenced incidence rates is modelled either with a first-order autoregressive process or with a Gaussian white-noise process depending on whether the system is in an epidemic or in a non-epidemic phase. The transition between phases of the disease is modelled as a Markovian process. Bayesian inference is carried out on the former model to detect influenza epidemics at the very moment of their onset. Moreover, the proposal provides the probability of being in an epidemic state at any given moment. In order to validate the methodology, a comparison of its performance with other alternatives has been made using influenza illness data obtained from the Sanitary Sentinel Network of the Comunitat Valenciana, one of the 17 autonomous regions in Spain.
DOI: 10.1002/sim.3320
PubMed: 18618414
Affiliations:
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Martínez-Beneito</name><affiliation wicri:level="2"><nlm:affiliation>Area de Epidemiología, Conselleria de Sanitat, Generalitat Valenciana, C/Micer Mascó 31, 46010 Valencia, Spain. miguel.a.martinez@uv.es</nlm:affiliation><country xml:lang="fr">Espagne</country><wicri:regionArea>Area de Epidemiología, Conselleria de Sanitat, Generalitat Valenciana, C/Micer Mascó 31, 46010 Valencia</wicri:regionArea><placeName><region nuts="2" type="communauté">Communauté valencienne</region></placeName></affiliation></author><author><name sortKey="Conesa, David" sort="Conesa, David" uniqKey="Conesa D" first="David" last="Conesa">David Conesa</name></author><author><name sortKey="L Pez Quilez, Antonio" sort="L Pez Quilez, Antonio" uniqKey="L Pez Quilez A" first="Antonio" last="L Pez-Quílez">Antonio L Pez-Quílez</name></author><author><name sortKey="L Pez Maside, Aurora" sort="L Pez Maside, Aurora" uniqKey="L Pez Maside A" first="Aurora" last="L Pez-Maside">Aurora L Pez-Maside</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2008">2008</date><idno type="RBID">pubmed:18618414</idno><idno type="pmid">18618414</idno><idno type="doi">10.1002/sim.3320</idno><idno type="wicri:Area/Main/Corpus">00538</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">00538</idno><idno type="wicri:Area/Main/Curation">000538</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000538</idno><idno type="wicri:Area/Main/Exploration">000538</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Bayesian Markov switching models for the early detection of influenza epidemics.</title><author><name sortKey="Martinez Beneito, Miguel A" sort="Martinez Beneito, Miguel A" uniqKey="Martinez Beneito M" first="Miguel A" last="Martínez-Beneito">Miguel A. Martínez-Beneito</name><affiliation wicri:level="2"><nlm:affiliation>Area de Epidemiología, Conselleria de Sanitat, Generalitat Valenciana, C/Micer Mascó 31, 46010 Valencia, Spain. miguel.a.martinez@uv.es</nlm:affiliation><country xml:lang="fr">Espagne</country><wicri:regionArea>Area de Epidemiología, Conselleria de Sanitat, Generalitat Valenciana, C/Micer Mascó 31, 46010 Valencia</wicri:regionArea><placeName><region nuts="2" type="communauté">Communauté valencienne</region></placeName></affiliation></author><author><name sortKey="Conesa, David" sort="Conesa, David" uniqKey="Conesa D" first="David" last="Conesa">David Conesa</name></author><author><name sortKey="L Pez Quilez, Antonio" sort="L Pez Quilez, Antonio" uniqKey="L Pez Quilez A" first="Antonio" last="L Pez-Quílez">Antonio L Pez-Quílez</name></author><author><name sortKey="L Pez Maside, Aurora" sort="L Pez Maside, Aurora" uniqKey="L Pez Maside A" first="Aurora" last="L Pez-Maside">Aurora L Pez-Maside</name></author></analytic><series><title level="j">Statistics in medicine</title><idno type="ISSN">0277-6715</idno><imprint><date when="2008" type="published">2008</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Bayes Theorem (MeSH)</term><term>Disease Outbreaks (MeSH)</term><term>Humans (MeSH)</term><term>Incidence (MeSH)</term><term>Influenza, Human (epidemiology)</term><term>Markov Chains (MeSH)</term><term>Models, Statistical (MeSH)</term><term>Regression Analysis (MeSH)</term><term>Sentinel Surveillance (MeSH)</term><term>Space-Time Clustering (MeSH)</term><term>Spain (epidemiology)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Agrégat spatio-temporel (MeSH)</term><term>Analyse de régression (MeSH)</term><term>Chaines de Markov (MeSH)</term><term>Espagne (épidémiologie)</term><term>Grippe humaine (épidémiologie)</term><term>Humains (MeSH)</term><term>Incidence (MeSH)</term><term>Modèles statistiques (MeSH)</term><term>Surveillance sentinelle (MeSH)</term><term>Théorème de Bayes (MeSH)</term><term>Épidémies de maladies (MeSH)</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Spain</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Espagne</term><term>Grippe humaine</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Bayes Theorem</term><term>Disease Outbreaks</term><term>Humans</term><term>Incidence</term><term>Markov Chains</term><term>Models, Statistical</term><term>Regression Analysis</term><term>Sentinel Surveillance</term><term>Space-Time Clustering</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Agrégat spatio-temporel</term><term>Analyse de régression</term><term>Chaines de Markov</term><term>Humains</term><term>Incidence</term><term>Modèles statistiques</term><term>Surveillance sentinelle</term><term>Théorème de Bayes</term><term>Épidémies de maladies</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Espagne</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The early detection of outbreaks of diseases is one of the most challenging objectives of epidemiological surveillance systems. In this paper, a Markov switching model is introduced to determine the epidemic and non-epidemic periods from influenza surveillance data: the process of differenced incidence rates is modelled either with a first-order autoregressive process or with a Gaussian white-noise process depending on whether the system is in an epidemic or in a non-epidemic phase. The transition between phases of the disease is modelled as a Markovian process. Bayesian inference is carried out on the former model to detect influenza epidemics at the very moment of their onset. Moreover, the proposal provides the probability of being in an epidemic state at any given moment. In order to validate the methodology, a comparison of its performance with other alternatives has been made using influenza illness data obtained from the Sanitary Sentinel Network of the Comunitat Valenciana, one of the 17 autonomous regions in Spain.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">18618414</PMID><DateCompleted><Year>2009</Year><Month>01</Month><Day>22</Day></DateCompleted><DateRevised><Year>2008</Year><Month>08</Month><Day>26</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">0277-6715</ISSN><JournalIssue CitedMedium="Print"><Volume>27</Volume><Issue>22</Issue><PubDate><Year>2008</Year><Month>Sep</Month><Day>30</Day></PubDate></JournalIssue><Title>Statistics in medicine</Title><ISOAbbreviation>Stat Med</ISOAbbreviation></Journal><ArticleTitle>Bayesian Markov switching models for the early detection of influenza epidemics.</ArticleTitle><Pagination><MedlinePgn>4455-68</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1002/sim.3320</ELocationID><Abstract><AbstractText>The early detection of outbreaks of diseases is one of the most challenging objectives of epidemiological surveillance systems. In this paper, a Markov switching model is introduced to determine the epidemic and non-epidemic periods from influenza surveillance data: the process of differenced incidence rates is modelled either with a first-order autoregressive process or with a Gaussian white-noise process depending on whether the system is in an epidemic or in a non-epidemic phase. The transition between phases of the disease is modelled as a Markovian process. Bayesian inference is carried out on the former model to detect influenza epidemics at the very moment of their onset. Moreover, the proposal provides the probability of being in an epidemic state at any given moment. In order to validate the methodology, a comparison of its performance with other alternatives has been made using influenza illness data obtained from the Sanitary Sentinel Network of the Comunitat Valenciana, one of the 17 autonomous regions in Spain.</AbstractText><CopyrightInformation>Copyright (c) 2008 John Wiley & Sons, Ltd.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Martínez-Beneito</LastName><ForeName>Miguel A</ForeName><Initials>MA</Initials><AffiliationInfo><Affiliation>Area de Epidemiología, Conselleria de Sanitat, Generalitat Valenciana, C/Micer Mascó 31, 46010 Valencia, Spain. miguel.a.martinez@uv.es</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Conesa</LastName><ForeName>David</ForeName><Initials>D</Initials></Author><Author ValidYN="Y"><LastName>López-Quílez</LastName><ForeName>Antonio</ForeName><Initials>A</Initials></Author><Author ValidYN="Y"><LastName>López-Maside</LastName><ForeName>Aurora</ForeName><Initials>A</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Stat Med</MedlineTA><NlmUniqueID>8215016</NlmUniqueID><ISSNLinking>0277-6715</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D001499" MajorTopicYN="Y">Bayes Theorem</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004196" MajorTopicYN="Y">Disease Outbreaks</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015994" MajorTopicYN="N">Incidence</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007251" MajorTopicYN="N">Influenza, Human</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008390" MajorTopicYN="Y">Markov Chains</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015233" MajorTopicYN="N">Models, Statistical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012044" MajorTopicYN="N">Regression Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018571" MajorTopicYN="N">Sentinel Surveillance</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013029" MajorTopicYN="N">Space-Time Clustering</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013030" MajorTopicYN="N" Type="Geographic">Spain</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="pubmed"><Year>2008</Year><Month>7</Month><Day>12</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2009</Year><Month>1</Month><Day>23</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2008</Year><Month>7</Month><Day>12</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">18618414</ArticleId><ArticleId IdType="doi">10.1002/sim.3320</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Espagne</li></country><region><li>Communauté valencienne</li></region></list><tree><noCountry><name sortKey="Conesa, David" sort="Conesa, David" uniqKey="Conesa D" first="David" last="Conesa">David Conesa</name><name sortKey="L Pez Maside, Aurora" sort="L Pez Maside, Aurora" uniqKey="L Pez Maside A" first="Aurora" last="L Pez-Maside">Aurora L Pez-Maside</name><name sortKey="L Pez Quilez, Antonio" sort="L Pez Quilez, Antonio" uniqKey="L Pez Quilez A" first="Antonio" last="L Pez-Quílez">Antonio L Pez-Quílez</name></noCountry><country name="Espagne"><region name="Communauté valencienne"><name sortKey="Martinez Beneito, Miguel A" sort="Martinez Beneito, Miguel A" uniqKey="Martinez Beneito M" first="Miguel A" last="Martínez-Beneito">Miguel A. 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