"Google flu trends" and emergency department triage data predicted the 2009 pandemic H1N1 waves in Manitoba.
Identifieur interne : 000C90 ( Main/Exploration ); précédent : 000C89; suivant : 000C91"Google flu trends" and emergency department triage data predicted the 2009 pandemic H1N1 waves in Manitoba.
Auteurs : Mohammad Tufail Malik [Canada] ; Abba Gumel ; Laura H. Thompson ; Trevor Strome ; Salaheddin M. MahmudSource :
- Canadian journal of public health = Revue canadienne de sante publique [ 0008-4263 ]
Descripteurs français
- KwdFr :
- MESH :
- organisation et administration : Service hospitalier d'urgences.
- virologie : Grippe humaine.
- épidémiologie : Grippe humaine, Manitoba.
- Flambées de maladies, Humains, Internet, Modèles linéaires, Sous-type H1N1 du virus de la grippe A, Surveillance de la population, Triage.
English descriptors
- KwdEn :
- MESH :
- geographic , epidemiology : Manitoba.
- epidemiology : Influenza, Human.
- organization & administration : Emergency Service, Hospital.
- virology : Influenza, Human.
- Disease Outbreaks, Humans, Influenza A Virus, H1N1 Subtype, Internet, Linear Models, Population Surveillance, Triage.
Abstract
OBJECTIVES
We assessed the performance of syndromic indicators based on Google Flu Trends (GFT) and emergency department (ED) data for the early detection and monitoring of the 2009 H1N1 pandemic waves in Manitoba.
METHODS
Time-series curves for the weekly counts of laboratory-confirmed H1N1 cases in Manitoba during the 2009 pandemic were plotted against the three syndromic indicators: 1) GFT data, based on flu-related Internet search queries, 2) weekly count of all ED visits triaged as influenza-like illness (ED ILI volume), and 3) percentage of all ED visits that were triaged as an ILI (ED ILI percent). A linear regression model was fitted separately for each indicator and correlations with weekly virologic data were calculated for different lag periods for each pandemic wave.
RESULTS
All three indicators peaked 1-2 weeks earlier than the epidemic curve of laboratory-confirmed cases. For GFT data, the best-fitting model had about a 2-week lag period in relation to the epidemic curve. Similarly, the best-fitting models for both ED indicators were observed for a time lag of 1-2 weeks. All three indicators performed better as predictors of the virologic time trends during the second wave as compared to the first. There was strong congruence between the time series of the GFT and both the ED ILI volume and the ED ILI percent indicators.
CONCLUSION
During an influenza season characterized by high levels of disease activity, GFT and ED indicators provided a good indication of weekly counts of laboratory-confirmed influenza cases in Manitoba 1-2 weeks in advance.
PubMed: 21913587
Affiliations:
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Thompson</name></author><author><name sortKey="Strome, Trevor" sort="Strome, Trevor" uniqKey="Strome T" first="Trevor" last="Strome">Trevor Strome</name></author><author><name sortKey="Mahmud, Salaheddin M" sort="Mahmud, Salaheddin M" uniqKey="Mahmud S" first="Salaheddin M" last="Mahmud">Salaheddin M. Mahmud</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="????"><PubDate><MedlineDate>2011 Jul-Aug</MedlineDate></PubDate></date><idno type="RBID">pubmed:21913587</idno><idno type="pmid">21913587</idno><idno type="wicri:Area/Main/Corpus">000497</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000497</idno><idno type="wicri:Area/Main/Curation">000497</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000497</idno><idno type="wicri:Area/Main/Exploration">000497</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">"Google flu trends" and emergency department triage data predicted the 2009 pandemic H1N1 waves in Manitoba.</title><author><name sortKey="Malik, Mohammad Tufail" sort="Malik, Mohammad Tufail" uniqKey="Malik M" first="Mohammad Tufail" last="Malik">Mohammad Tufail Malik</name><affiliation wicri:level="4"><nlm:affiliation>Department of Mathematics, University of Manitoba, Winnipeg, MB.</nlm:affiliation><orgName type="university">Université du Manitoba</orgName><country>Canada</country><placeName><settlement type="city">Winnipeg</settlement><region type="state">Manitoba</region></placeName></affiliation></author><author><name sortKey="Gumel, Abba" sort="Gumel, Abba" uniqKey="Gumel A" first="Abba" last="Gumel">Abba Gumel</name></author><author><name sortKey="Thompson, Laura H" sort="Thompson, Laura H" uniqKey="Thompson L" first="Laura H" last="Thompson">Laura H. Thompson</name></author><author><name sortKey="Strome, Trevor" sort="Strome, Trevor" uniqKey="Strome T" first="Trevor" last="Strome">Trevor Strome</name></author><author><name sortKey="Mahmud, Salaheddin M" sort="Mahmud, Salaheddin M" uniqKey="Mahmud S" first="Salaheddin M" last="Mahmud">Salaheddin M. Mahmud</name></author></analytic><series><title level="j">Canadian journal of public health = Revue canadienne de sante publique</title><idno type="ISSN">0008-4263</idno></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Disease Outbreaks</term><term>Emergency Service, Hospital (organization & administration)</term><term>Humans</term><term>Influenza A Virus, H1N1 Subtype</term><term>Influenza, Human (epidemiology)</term><term>Influenza, Human (virology)</term><term>Internet</term><term>Linear Models</term><term>Manitoba (epidemiology)</term><term>Population Surveillance</term><term>Triage</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Flambées de maladies</term><term>Grippe humaine (virologie)</term><term>Grippe humaine (épidémiologie)</term><term>Humains</term><term>Internet</term><term>Manitoba (épidémiologie)</term><term>Modèles linéaires</term><term>Service hospitalier d'urgences (organisation et administration)</term><term>Sous-type H1N1 du virus de la grippe A</term><term>Surveillance de la population</term><term>Triage</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Manitoba</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="organisation et administration" xml:lang="fr"><term>Service hospitalier d'urgences</term></keywords><keywords scheme="MESH" qualifier="organization & administration" xml:lang="en"><term>Emergency Service, Hospital</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>Manitoba</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Disease Outbreaks</term><term>Humans</term><term>Influenza A Virus, H1N1 Subtype</term><term>Internet</term><term>Linear Models</term><term>Population Surveillance</term><term>Triage</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Flambées de maladies</term><term>Humains</term><term>Internet</term><term>Modèles linéaires</term><term>Sous-type H1N1 du virus de la grippe A</term><term>Surveillance de la population</term><term>Triage</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>OBJECTIVES</b></p><p>We assessed the performance of syndromic indicators based on Google Flu Trends (GFT) and emergency department (ED) data for the early detection and monitoring of the 2009 H1N1 pandemic waves in Manitoba.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>Time-series curves for the weekly counts of laboratory-confirmed H1N1 cases in Manitoba during the 2009 pandemic were plotted against the three syndromic indicators: 1) GFT data, based on flu-related Internet search queries, 2) weekly count of all ED visits triaged as influenza-like illness (ED ILI volume), and 3) percentage of all ED visits that were triaged as an ILI (ED ILI percent). A linear regression model was fitted separately for each indicator and correlations with weekly virologic data were calculated for different lag periods for each pandemic wave.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>All three indicators peaked 1-2 weeks earlier than the epidemic curve of laboratory-confirmed cases. For GFT data, the best-fitting model had about a 2-week lag period in relation to the epidemic curve. Similarly, the best-fitting models for both ED indicators were observed for a time lag of 1-2 weeks. All three indicators performed better as predictors of the virologic time trends during the second wave as compared to the first. There was strong congruence between the time series of the GFT and both the ED ILI volume and the ED ILI percent indicators.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSION</b></p><p>During an influenza season characterized by high levels of disease activity, GFT and ED indicators provided a good indication of weekly counts of laboratory-confirmed influenza cases in Manitoba 1-2 weeks in advance.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">21913587</PMID><DateCompleted><Year>2011</Year><Month>11</Month><Day>02</Day></DateCompleted><DateRevised><Year>2020</Year><Month>02</Month><Day>05</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">0008-4263</ISSN><JournalIssue CitedMedium="Print"><Volume>102</Volume><Issue>4</Issue><PubDate><MedlineDate>2011 Jul-Aug</MedlineDate></PubDate></JournalIssue><Title>Canadian journal of public health = Revue canadienne de sante publique</Title><ISOAbbreviation>Can J Public Health</ISOAbbreviation></Journal><ArticleTitle>"Google flu trends" and emergency department triage data predicted the 2009 pandemic H1N1 waves in Manitoba.</ArticleTitle><Pagination><MedlinePgn>294-7</MedlinePgn></Pagination><Abstract><AbstractText Label="OBJECTIVES" NlmCategory="OBJECTIVE">We assessed the performance of syndromic indicators based on Google Flu Trends (GFT) and emergency department (ED) data for the early detection and monitoring of the 2009 H1N1 pandemic waves in Manitoba.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">Time-series curves for the weekly counts of laboratory-confirmed H1N1 cases in Manitoba during the 2009 pandemic were plotted against the three syndromic indicators: 1) GFT data, based on flu-related Internet search queries, 2) weekly count of all ED visits triaged as influenza-like illness (ED ILI volume), and 3) percentage of all ED visits that were triaged as an ILI (ED ILI percent). A linear regression model was fitted separately for each indicator and correlations with weekly virologic data were calculated for different lag periods for each pandemic wave.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">All three indicators peaked 1-2 weeks earlier than the epidemic curve of laboratory-confirmed cases. For GFT data, the best-fitting model had about a 2-week lag period in relation to the epidemic curve. Similarly, the best-fitting models for both ED indicators were observed for a time lag of 1-2 weeks. All three indicators performed better as predictors of the virologic time trends during the second wave as compared to the first. There was strong congruence between the time series of the GFT and both the ED ILI volume and the ED ILI percent indicators.</AbstractText><AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">During an influenza season characterized by high levels of disease activity, GFT and ED indicators provided a good indication of weekly counts of laboratory-confirmed influenza cases in Manitoba 1-2 weeks in advance.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Malik</LastName><ForeName>Mohammad Tufail</ForeName><Initials>MT</Initials><AffiliationInfo><Affiliation>Department of Mathematics, University of Manitoba, Winnipeg, MB.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gumel</LastName><ForeName>Abba</ForeName><Initials>A</Initials></Author><Author ValidYN="Y"><LastName>Thompson</LastName><ForeName>Laura H</ForeName><Initials>LH</Initials></Author><Author ValidYN="Y"><LastName>Strome</LastName><ForeName>Trevor</ForeName><Initials>T</Initials></Author><Author ValidYN="Y"><LastName>Mahmud</LastName><ForeName>Salaheddin M</ForeName><Initials>SM</Initials></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>/PTL-97126</GrantID><Agency>Canadian Institutes of Health Research</Agency><Country>Canada</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Can J Public Health</MedlineTA><NlmUniqueID>0372714</NlmUniqueID><ISSNLinking>0008-4263</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D004196" MajorTopicYN="N">Disease Outbreaks</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004636" 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Mahmud</name><name sortKey="Strome, Trevor" sort="Strome, Trevor" uniqKey="Strome T" first="Trevor" last="Strome">Trevor Strome</name><name sortKey="Thompson, Laura H" sort="Thompson, Laura H" uniqKey="Thompson L" first="Laura H" last="Thompson">Laura H. Thompson</name></noCountry><country name="Canada"><region name="Manitoba"><name sortKey="Malik, Mohammad Tufail" sort="Malik, Mohammad Tufail" uniqKey="Malik M" first="Mohammad Tufail" last="Malik">Mohammad Tufail Malik</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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