Performances of statistical methods for the detection of seasonal influenza epidemics using a consensus-based gold standard.
Identifieur interne : 000076 ( Main/Exploration ); précédent : 000075; suivant : 000077Performances of statistical methods for the detection of seasonal influenza epidemics using a consensus-based gold standard.
Auteurs : C. Souty [France] ; R. Jreich [France] ; Y. Le Strat [France] ; C. Pelat [France] ; P Y Boëlle [France] ; C. Guerrisi [France] ; S. Masse [France] ; T. Blanchon [France] ; T. Hanslik [France] ; C. Turbelin [France]Source :
- Epidemiology and infection [ 1469-4409 ] ; 2018.
Descripteurs français
- KwdFr :
- MESH :
- épidémiologie : France, Grippe humaine.
- Algorithmes, Analyse de régression, Humains, Incidence, Saisons, Statistiques comme sujet, Surveillance épidémiologique, Épidémies.
English descriptors
- KwdEn :
- MESH :
- epidemiology : France, Influenza, Human.
- Algorithms, Epidemics, Epidemiological Monitoring, Humans, Incidence, Regression Analysis, Seasons, Statistics as Topic.
Abstract
Influenza epidemics are monitored using influenza-like illness (ILI) data reported by health-care professionals. Timely detection of the onset of epidemics is often performed by applying a statistical method on weekly ILI incidence estimates with a large range of methods used worldwide. However, performance evaluation and comparison of these algorithms is hindered by: (1) the absence of a gold standard regarding influenza epidemic periods and (2) the absence of consensual evaluation criteria. As of now, performance evaluations metrics are based only on sensitivity, specificity and timeliness of detection, since definitions are not clear for time-repeated measurements such as weekly epidemic detection. We aimed to evaluate several epidemic detection methods by comparing their alerts to a gold standard determined by international expert consensus. We introduced new performance metrics that meet important objective of influenza surveillance in temperate countries: to detect accurately the start of the single epidemic period each year. Evaluations are presented using ILI incidence in France between 1995 and 2011. We found that the two performance metrics defined allowed discrimination between epidemic detection methods. In the context of performance detection evaluation, other metrics used commonly than the standard could better achieve the needs of real-time influenza surveillance.
DOI: 10.1017/S095026881700276X
PubMed: 29208062
Affiliations:
Links toward previous steps (curation, corpus...)
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Guerrisi</name><affiliation wicri:level="3"><nlm:affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Masse, S" sort="Masse, S" uniqKey="Masse S" first="S" last="Masse">S. Masse</name><affiliation wicri:level="3"><nlm:affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Blanchon, T" sort="Blanchon, T" uniqKey="Blanchon T" first="T" last="Blanchon">T. Blanchon</name><affiliation wicri:level="3"><nlm:affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Hanslik, T" sort="Hanslik, T" uniqKey="Hanslik T" first="T" last="Hanslik">T. Hanslik</name><affiliation wicri:level="3"><nlm:affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Turbelin, C" sort="Turbelin, C" uniqKey="Turbelin C" first="C" last="Turbelin">C. Turbelin</name><affiliation wicri:level="3"><nlm:affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2018">2018</date><idno type="RBID">pubmed:29208062</idno><idno type="pmid">29208062</idno><idno type="doi">10.1017/S095026881700276X</idno><idno type="wicri:Area/Main/Corpus">000090</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000090</idno><idno type="wicri:Area/Main/Curation">000090</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000090</idno><idno type="wicri:Area/Main/Exploration">000090</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Performances of statistical methods for the detection of seasonal influenza epidemics using a consensus-based gold standard.</title><author><name sortKey="Souty, C" sort="Souty, C" uniqKey="Souty C" first="C" last="Souty">C. Souty</name><affiliation wicri:level="3"><nlm:affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Jreich, R" sort="Jreich, R" uniqKey="Jreich R" first="R" last="Jreich">R. Jreich</name><affiliation wicri:level="3"><nlm:affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Le Strat, Y" sort="Le Strat, Y" uniqKey="Le Strat Y" first="Y" last="Le Strat">Y. Le Strat</name><affiliation wicri:level="3"><nlm:affiliation>Santé publique France,French national public health agency,F-94415,Saint-Maurice,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Santé publique France,French national public health agency,F-94415,Saint-Maurice</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Pelat, C" sort="Pelat, C" uniqKey="Pelat C" first="C" last="Pelat">C. Pelat</name><affiliation wicri:level="3"><nlm:affiliation>Santé publique France,French national public health agency,F-94415,Saint-Maurice,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Santé publique France,French national public health agency,F-94415,Saint-Maurice</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Boelle, P Y" sort="Boelle, P Y" uniqKey="Boelle P" first="P Y" last="Boëlle">P Y Boëlle</name><affiliation wicri:level="3"><nlm:affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Guerrisi, C" sort="Guerrisi, C" uniqKey="Guerrisi C" first="C" last="Guerrisi">C. Guerrisi</name><affiliation wicri:level="3"><nlm:affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Masse, S" sort="Masse, S" uniqKey="Masse S" first="S" last="Masse">S. Masse</name><affiliation wicri:level="3"><nlm:affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Blanchon, T" sort="Blanchon, T" uniqKey="Blanchon T" first="T" last="Blanchon">T. Blanchon</name><affiliation wicri:level="3"><nlm:affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Hanslik, T" sort="Hanslik, T" uniqKey="Hanslik T" first="T" last="Hanslik">T. Hanslik</name><affiliation wicri:level="3"><nlm:affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Turbelin, C" sort="Turbelin, C" uniqKey="Turbelin C" first="C" last="Turbelin">C. Turbelin</name><affiliation wicri:level="3"><nlm:affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author></analytic><series><title level="j">Epidemiology and infection</title><idno type="eISSN">1469-4409</idno><imprint><date when="2018" type="published">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms (MeSH)</term><term>Epidemics (MeSH)</term><term>Epidemiological Monitoring (MeSH)</term><term>France (epidemiology)</term><term>Humans (MeSH)</term><term>Incidence (MeSH)</term><term>Influenza, Human (epidemiology)</term><term>Regression Analysis (MeSH)</term><term>Seasons (MeSH)</term><term>Statistics as Topic (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes (MeSH)</term><term>Analyse de régression (MeSH)</term><term>France (épidémiologie)</term><term>Grippe humaine (épidémiologie)</term><term>Humains (MeSH)</term><term>Incidence (MeSH)</term><term>Saisons (MeSH)</term><term>Statistiques comme sujet (MeSH)</term><term>Surveillance épidémiologique (MeSH)</term><term>Épidémies (MeSH)</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>France</term><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>France</term><term>Grippe humaine</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Epidemics</term><term>Epidemiological Monitoring</term><term>Humans</term><term>Incidence</term><term>Regression Analysis</term><term>Seasons</term><term>Statistics as Topic</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Analyse de régression</term><term>Humains</term><term>Incidence</term><term>Saisons</term><term>Statistiques comme sujet</term><term>Surveillance épidémiologique</term><term>Épidémies</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Influenza epidemics are monitored using influenza-like illness (ILI) data reported by health-care professionals. Timely detection of the onset of epidemics is often performed by applying a statistical method on weekly ILI incidence estimates with a large range of methods used worldwide. However, performance evaluation and comparison of these algorithms is hindered by: (1) the absence of a gold standard regarding influenza epidemic periods and (2) the absence of consensual evaluation criteria. As of now, performance evaluations metrics are based only on sensitivity, specificity and timeliness of detection, since definitions are not clear for time-repeated measurements such as weekly epidemic detection. We aimed to evaluate several epidemic detection methods by comparing their alerts to a gold standard determined by international expert consensus. We introduced new performance metrics that meet important objective of influenza surveillance in temperate countries: to detect accurately the start of the single epidemic period each year. Evaluations are presented using ILI incidence in France between 1995 and 2011. We found that the two performance metrics defined allowed discrimination between epidemic detection methods. In the context of performance detection evaluation, other metrics used commonly than the standard could better achieve the needs of real-time influenza surveillance.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">29208062</PMID><DateCompleted><Year>2018</Year><Month>10</Month><Day>29</Day></DateCompleted><DateRevised><Year>2018</Year><Month>10</Month><Day>29</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1469-4409</ISSN><JournalIssue CitedMedium="Internet"><Volume>146</Volume><Issue>2</Issue><PubDate><Year>2018</Year><Month>01</Month></PubDate></JournalIssue><Title>Epidemiology and infection</Title><ISOAbbreviation>Epidemiol. Infect.</ISOAbbreviation></Journal><ArticleTitle>Performances of statistical methods for the detection of seasonal influenza epidemics using a consensus-based gold standard.</ArticleTitle><Pagination><MedlinePgn>168-176</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1017/S095026881700276X</ELocationID><Abstract><AbstractText>Influenza epidemics are monitored using influenza-like illness (ILI) data reported by health-care professionals. Timely detection of the onset of epidemics is often performed by applying a statistical method on weekly ILI incidence estimates with a large range of methods used worldwide. However, performance evaluation and comparison of these algorithms is hindered by: (1) the absence of a gold standard regarding influenza epidemic periods and (2) the absence of consensual evaluation criteria. As of now, performance evaluations metrics are based only on sensitivity, specificity and timeliness of detection, since definitions are not clear for time-repeated measurements such as weekly epidemic detection. We aimed to evaluate several epidemic detection methods by comparing their alerts to a gold standard determined by international expert consensus. We introduced new performance metrics that meet important objective of influenza surveillance in temperate countries: to detect accurately the start of the single epidemic period each year. Evaluations are presented using ILI incidence in France between 1995 and 2011. We found that the two performance metrics defined allowed discrimination between epidemic detection methods. In the context of performance detection evaluation, other metrics used commonly than the standard could better achieve the needs of real-time influenza surveillance.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Souty</LastName><ForeName>C</ForeName><Initials>C</Initials><Identifier Source="ORCID">0000-0002-4990-5201</Identifier><AffiliationInfo><Affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jreich</LastName><ForeName>R</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>LE Strat</LastName><ForeName>Y</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Santé publique France,French national public health agency,F-94415,Saint-Maurice,France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Pelat</LastName><ForeName>C</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Santé publique France,French national public health agency,F-94415,Saint-Maurice,France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Boëlle</LastName><ForeName>P Y</ForeName><Initials>PY</Initials><AffiliationInfo><Affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Guerrisi</LastName><ForeName>C</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Masse</LastName><ForeName>S</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Blanchon</LastName><ForeName>T</ForeName><Initials>T</Initials><AffiliationInfo><Affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hanslik</LastName><ForeName>T</ForeName><Initials>T</Initials><AffiliationInfo><Affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Turbelin</LastName><ForeName>C</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Sorbonne Universités,UPMC Univ Paris 06,INSERM,Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136),F-75012,Paris,France.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2017</Year><Month>12</Month><Day>06</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Epidemiol Infect</MedlineTA><NlmUniqueID>8703737</NlmUniqueID><ISSNLinking>0950-2688</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000465" MajorTopicYN="Y">Algorithms</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058872" MajorTopicYN="Y">Epidemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D062665" MajorTopicYN="Y">Epidemiological Monitoring</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005602" MajorTopicYN="N">France</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></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="D012044" MajorTopicYN="N">Regression Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012621" MajorTopicYN="N">Seasons</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013223" MajorTopicYN="Y">Statistics as Topic</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">Epidemics</Keyword><Keyword MajorTopicYN="Y">influenza</Keyword><Keyword MajorTopicYN="Y">outbreaks</Keyword><Keyword MajorTopicYN="Y">surveillance</Keyword><Keyword MajorTopicYN="Y">surveillance system</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="pubmed"><Year>2017</Year><Month>12</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2018</Year><Month>10</Month><Day>30</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2017</Year><Month>12</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">29208062</ArticleId><ArticleId IdType="pii">S095026881700276X</ArticleId><ArticleId IdType="doi">10.1017/S095026881700276X</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>France</li></country><region><li>Île-de-France</li></region></list><tree><country name="France"><region name="Île-de-France"><name sortKey="Souty, C" sort="Souty, C" uniqKey="Souty C" first="C" last="Souty">C. Souty</name></region><name sortKey="Blanchon, T" sort="Blanchon, T" uniqKey="Blanchon T" first="T" last="Blanchon">T. Blanchon</name><name sortKey="Boelle, P Y" sort="Boelle, P Y" uniqKey="Boelle P" first="P Y" last="Boëlle">P Y Boëlle</name><name sortKey="Guerrisi, C" sort="Guerrisi, C" uniqKey="Guerrisi C" first="C" last="Guerrisi">C. Guerrisi</name><name sortKey="Hanslik, T" sort="Hanslik, T" uniqKey="Hanslik T" first="T" last="Hanslik">T. Hanslik</name><name sortKey="Jreich, R" sort="Jreich, R" uniqKey="Jreich R" first="R" last="Jreich">R. Jreich</name><name sortKey="Le Strat, Y" sort="Le Strat, Y" uniqKey="Le Strat Y" first="Y" last="Le Strat">Y. Le Strat</name><name sortKey="Masse, S" sort="Masse, S" uniqKey="Masse S" first="S" last="Masse">S. Masse</name><name sortKey="Pelat, C" sort="Pelat, C" uniqKey="Pelat C" first="C" last="Pelat">C. Pelat</name><name sortKey="Turbelin, C" sort="Turbelin, C" uniqKey="Turbelin C" first="C" last="Turbelin">C. Turbelin</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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