Multivariate modelling of infectious disease surveillance data.
Identifieur interne : 000435 ( Main/Exploration ); précédent : 000434; suivant : 000436Multivariate modelling of infectious disease surveillance data.
Auteurs : M. Paul [Suisse] ; L. Held ; A M ToschkeSource :
- Statistics in medicine [ 1097-0258 ] ; 2008.
Descripteurs français
- KwdFr :
- Allemagne (épidémiologie), Analyse multivariée, Biométrie (), Flambées de maladies (), Fonctions de vraisemblance, Grippe humaine (épidémiologie), Humains, Infections à méningocoques (épidémiologie), Interprétation statistique de données, Maladies transmissibles (épidémiologie), Modèles statistiques, Méthodes épidémiologiques, Surveillance de la population, États-Unis d'Amérique (épidémiologie).
- MESH :
- épidémiologie : Allemagne, Grippe humaine, Infections à méningocoques, Maladies transmissibles, États-Unis d'Amérique.
- Analyse multivariée, Biométrie, Flambées de maladies, Fonctions de vraisemblance, Humains, Interprétation statistique de données, Modèles statistiques, Méthodes épidémiologiques, Surveillance de la population.
- Wicri :
- geographic : Allemagne, États-Unis.
English descriptors
- KwdEn :
- Biometry (methods), Communicable Diseases (epidemiology), Data Interpretation, Statistical, Disease Outbreaks (statistics & numerical data), Epidemiologic Methods, Germany (epidemiology), Humans, Influenza, Human (epidemiology), Likelihood Functions, Meningococcal Infections (epidemiology), Models, Statistical, Multivariate Analysis, Population Surveillance, United States (epidemiology).
- MESH :
- geographic , epidemiology : Germany, United States.
- epidemiology : Communicable Diseases, Influenza, Human, Meningococcal Infections.
- methods : Biometry.
- statistics & numerical data : Disease Outbreaks.
- Data Interpretation, Statistical, Epidemiologic Methods, Humans, Likelihood Functions, Models, Statistical, Multivariate Analysis, Population Surveillance.
Abstract
This paper describes a model-based approach to analyse multivariate time series data on counts of infectious diseases. It extends a method previously described in the literature to deal with possible dependence between disease counts from different pathogens. In a spatio-temporal context it is proposed to include additional information on global dispersal of the pathogen in the model. Two examples are given: the first describes an analysis of weekly influenza and meningococcal disease counts from Germany. The second gives an analysis of the spatio-temporal spread of influenza in the U.S.A., 1996-2006, using air traffic information. Maximum likelihood estimates in this non-standard model class are obtained using general optimization routines, which are integrated in the R package surveillance.
DOI: 10.1002/sim.3440
PubMed: 18800337
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Multivariate modelling of infectious disease surveillance data.</title><author><name sortKey="Paul, M" sort="Paul, M" uniqKey="Paul M" first="M" last="Paul">M. Paul</name><affiliation wicri:level="4"><nlm:affiliation>Biostatistics Unit, Institute of Social and Preventive Medicine, University of Zurich, Zurich, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Biostatistics Unit, Institute of Social and Preventive Medicine, University of Zurich, Zurich</wicri:regionArea><orgName type="university">Université de Zurich</orgName><placeName><settlement type="city">Zurich</settlement><region nuts="3" type="region">Canton de Zurich</region></placeName></affiliation></author><author><name sortKey="Held, L" sort="Held, L" uniqKey="Held L" first="L" last="Held">L. Held</name></author><author><name sortKey="Toschke, A M" sort="Toschke, A M" uniqKey="Toschke A" first="A M" last="Toschke">A M Toschke</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2008">2008</date><idno type="RBID">pubmed:18800337</idno><idno type="pmid">18800337</idno><idno type="doi">10.1002/sim.3440</idno><idno type="wicri:Area/Main/Corpus">000431</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000431</idno><idno type="wicri:Area/Main/Curation">000431</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000431</idno><idno type="wicri:Area/Main/Exploration">000431</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Multivariate modelling of infectious disease surveillance data.</title><author><name sortKey="Paul, M" sort="Paul, M" uniqKey="Paul M" first="M" last="Paul">M. Paul</name><affiliation wicri:level="4"><nlm:affiliation>Biostatistics Unit, Institute of Social and Preventive Medicine, University of Zurich, Zurich, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Biostatistics Unit, Institute of Social and Preventive Medicine, University of Zurich, Zurich</wicri:regionArea><orgName type="university">Université de Zurich</orgName><placeName><settlement type="city">Zurich</settlement><region nuts="3" type="region">Canton de Zurich</region></placeName></affiliation></author><author><name sortKey="Held, L" sort="Held, L" uniqKey="Held L" first="L" last="Held">L. Held</name></author><author><name sortKey="Toschke, A M" sort="Toschke, A M" uniqKey="Toschke A" first="A M" last="Toschke">A M Toschke</name></author></analytic><series><title level="j">Statistics in medicine</title><idno type="eISSN">1097-0258</idno><imprint><date when="2008" type="published">2008</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Biometry (methods)</term><term>Communicable Diseases (epidemiology)</term><term>Data Interpretation, Statistical</term><term>Disease Outbreaks (statistics & numerical data)</term><term>Epidemiologic Methods</term><term>Germany (epidemiology)</term><term>Humans</term><term>Influenza, Human (epidemiology)</term><term>Likelihood Functions</term><term>Meningococcal Infections (epidemiology)</term><term>Models, Statistical</term><term>Multivariate Analysis</term><term>Population Surveillance</term><term>United States (epidemiology)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Allemagne (épidémiologie)</term><term>Analyse multivariée</term><term>Biométrie ()</term><term>Flambées de maladies ()</term><term>Fonctions de vraisemblance</term><term>Grippe humaine (épidémiologie)</term><term>Humains</term><term>Infections à méningocoques (épidémiologie)</term><term>Interprétation statistique de données</term><term>Maladies transmissibles (épidémiologie)</term><term>Modèles statistiques</term><term>Méthodes épidémiologiques</term><term>Surveillance de la population</term><term>États-Unis d'Amérique (épidémiologie)</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Germany</term><term>United States</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Communicable Diseases</term><term>Influenza, Human</term><term>Meningococcal Infections</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Biometry</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Disease Outbreaks</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Allemagne</term><term>Grippe humaine</term><term>Infections à méningocoques</term><term>Maladies transmissibles</term><term>États-Unis d'Amérique</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Data Interpretation, Statistical</term><term>Epidemiologic Methods</term><term>Humans</term><term>Likelihood Functions</term><term>Models, Statistical</term><term>Multivariate Analysis</term><term>Population Surveillance</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Analyse multivariée</term><term>Biométrie</term><term>Flambées de maladies</term><term>Fonctions de vraisemblance</term><term>Humains</term><term>Interprétation statistique de données</term><term>Modèles statistiques</term><term>Méthodes épidémiologiques</term><term>Surveillance de la population</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Allemagne</term><term>États-Unis</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">This paper describes a model-based approach to analyse multivariate time series data on counts of infectious diseases. It extends a method previously described in the literature to deal with possible dependence between disease counts from different pathogens. In a spatio-temporal context it is proposed to include additional information on global dispersal of the pathogen in the model. Two examples are given: the first describes an analysis of weekly influenza and meningococcal disease counts from Germany. The second gives an analysis of the spatio-temporal spread of influenza in the U.S.A., 1996-2006, using air traffic information. Maximum likelihood estimates in this non-standard model class are obtained using general optimization routines, which are integrated in the R package surveillance.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">18800337</PMID><DateCompleted><Year>2009</Year><Month>07</Month><Day>17</Day></DateCompleted><DateRevised><Year>2009</Year><Month>07</Month><Day>30</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Electronic">1097-0258</ISSN><JournalIssue CitedMedium="Internet"><Volume>27</Volume><Issue>29</Issue><PubDate><Year>2008</Year><Month>Dec</Month><Day>20</Day></PubDate></JournalIssue><Title>Statistics in medicine</Title><ISOAbbreviation>Stat Med</ISOAbbreviation></Journal><ArticleTitle>Multivariate modelling of infectious disease surveillance data.</ArticleTitle><Pagination><MedlinePgn>6250-67</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1002/sim.3440</ELocationID><Abstract><AbstractText>This paper describes a model-based approach to analyse multivariate time series data on counts of infectious diseases. It extends a method previously described in the literature to deal with possible dependence between disease counts from different pathogens. In a spatio-temporal context it is proposed to include additional information on global dispersal of the pathogen in the model. Two examples are given: the first describes an analysis of weekly influenza and meningococcal disease counts from Germany. The second gives an analysis of the spatio-temporal spread of influenza in the U.S.A., 1996-2006, using air traffic information. Maximum likelihood estimates in this non-standard model class are obtained using general optimization routines, which are integrated in the R package surveillance.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Paul</LastName><ForeName>M</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Biostatistics Unit, Institute of Social and Preventive Medicine, University of Zurich, Zurich, Switzerland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Held</LastName><ForeName>L</ForeName><Initials>L</Initials></Author><Author ValidYN="Y"><LastName>Toschke</LastName><ForeName>A M</ForeName><Initials>AM</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="D001699" MajorTopicYN="N">Biometry</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D003141" MajorTopicYN="N">Communicable Diseases</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D003627" MajorTopicYN="N">Data Interpretation, Statistical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004196" MajorTopicYN="N">Disease Outbreaks</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D004812" MajorTopicYN="N">Epidemiologic Methods</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005858" MajorTopicYN="N" Type="Geographic">Germany</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007251" MajorTopicYN="N">Influenza, Human</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D016013" MajorTopicYN="N">Likelihood Functions</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008589" MajorTopicYN="N">Meningococcal Infections</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D015233" MajorTopicYN="N">Models, Statistical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015999" MajorTopicYN="N">Multivariate Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011159" MajorTopicYN="N">Population Surveillance</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014481" MajorTopicYN="N" Type="Geographic">United States</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="pubmed"><Year>2008</Year><Month>9</Month><Day>19</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2009</Year><Month>7</Month><Day>18</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2008</Year><Month>9</Month><Day>19</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">18800337</ArticleId><ArticleId IdType="doi">10.1002/sim.3440</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Suisse</li></country><region><li>Canton de Zurich</li></region><settlement><li>Zurich</li></settlement><orgName><li>Université de Zurich</li></orgName></list><tree><noCountry><name sortKey="Held, L" sort="Held, L" uniqKey="Held L" first="L" last="Held">L. Held</name><name sortKey="Toschke, A M" sort="Toschke, A M" uniqKey="Toschke A" first="A M" last="Toschke">A M Toschke</name></noCountry><country name="Suisse"><region name="Canton de Zurich"><name sortKey="Paul, M" sort="Paul, M" uniqKey="Paul M" first="M" last="Paul">M. Paul</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Sante/explor/GrippeAllemagneV3/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000435 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000435 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Sante
|area= GrippeAllemagneV3
|flux= Main
|étape= Exploration
|type= RBID
|clé= pubmed:18800337
|texte= Multivariate modelling of infectious disease surveillance data.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i -Sk "pubmed:18800337" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd \
| NlmPubMed2Wicri -a GrippeAllemagneV3
| This area was generated with Dilib version V0.6.35. |  |