Emergency department and 'Google flu trends' data as syndromic surveillance indicators for seasonal influenza.
Identifieur interne : 000291 ( Main/Corpus ); précédent : 000290; suivant : 000292Emergency department and 'Google flu trends' data as syndromic surveillance indicators for seasonal influenza.
Auteurs : L H Thompson ; M T Malik ; A. Gumel ; T. Strome ; S M MahmudSource :
- Epidemiology and infection [ 1469-4409 ] ; 2014.
English descriptors
- KwdEn :
- Databases, Factual, Disease Outbreaks, Emergency Service, Hospital (statistics & numerical data), Female, Humans, Incidence, Influenza, Human (diagnosis), Influenza, Human (epidemiology), Influenza, Human (therapy), Internet, Linear Models, Male, Manitoba (epidemiology), Population Surveillance (methods), Severity of Illness Index.
- MESH :
- diagnosis : Influenza, Human.
- epidemiology : Influenza, Human, Manitoba.
- methods : Population Surveillance.
- statistics & numerical data : Emergency Service, Hospital.
- therapy : Influenza, Human.
- Databases, Factual, Disease Outbreaks, Female, Humans, Incidence, Internet, Linear Models, Male, Severity of Illness Index.
Abstract
We evaluated syndromic indicators of influenza disease activity developed using emergency department (ED) data - total ED visits attributed to influenza-like illness (ILI) ('ED ILI volume') and percentage of visits attributed to ILI ('ED ILI percent') - and Google flu trends (GFT) data (ILI cases/100 000 physician visits). Congruity and correlation among these indicators and between these indicators and weekly count of laboratory-confirmed influenza in Manitoba was assessed graphically using linear regression models. Both ED and GFT data performed well as syndromic indicators of influenza activity, and were highly correlated with each other in real time. The strongest correlations between virological data and ED ILI volume and ED ILI percent, respectively, were 0·77 and 0·71. The strongest correlation of GFT was 0·74. Seasonal influenza activity may be effectively monitored using ED and GFT data.
DOI: 10.1017/S0950268813003464
PubMed: 24480399
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pubmed:24480399Le document en format XML
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Gumel</name><affiliation><nlm:affiliation>Department of Mathematics,University of Manitoba,Winnipeg, MB,Canada.</nlm:affiliation></affiliation></author><author><name sortKey="Strome, T" sort="Strome, T" uniqKey="Strome T" first="T" last="Strome">T. Strome</name><affiliation><nlm:affiliation>Department of Emergency Medicine,University of Manitoba,Winnipeg, MB,Canada.</nlm:affiliation></affiliation></author><author><name sortKey="Mahmud, S M" sort="Mahmud, S M" uniqKey="Mahmud S" first="S M" last="Mahmud">S M Mahmud</name><affiliation><nlm:affiliation>Department of Community Health Sciences,University of Manitoba,Winnipeg, MB,Canada.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2014">2014</date><idno type="RBID">pubmed:24480399</idno><idno type="pmid">24480399</idno><idno type="doi">10.1017/S0950268813003464</idno><idno type="wicri:Area/Main/Corpus">000291</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000291</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Emergency department and 'Google flu trends' data as syndromic surveillance indicators for seasonal influenza.</title><author><name sortKey="Thompson, L H" sort="Thompson, L H" uniqKey="Thompson L" first="L H" last="Thompson">L H Thompson</name><affiliation><nlm:affiliation>Department of Community Health Sciences,University of Manitoba,Winnipeg, MB,Canada.</nlm:affiliation></affiliation></author><author><name sortKey="Malik, M T" sort="Malik, M T" uniqKey="Malik M" first="M T" last="Malik">M T Malik</name><affiliation><nlm:affiliation>Department of Community Health Sciences,University of Manitoba,Winnipeg, MB,Canada.</nlm:affiliation></affiliation></author><author><name sortKey="Gumel, A" sort="Gumel, A" uniqKey="Gumel A" first="A" last="Gumel">A. Gumel</name><affiliation><nlm:affiliation>Department of Mathematics,University of Manitoba,Winnipeg, MB,Canada.</nlm:affiliation></affiliation></author><author><name sortKey="Strome, T" sort="Strome, T" uniqKey="Strome T" first="T" last="Strome">T. Strome</name><affiliation><nlm:affiliation>Department of Emergency Medicine,University of Manitoba,Winnipeg, MB,Canada.</nlm:affiliation></affiliation></author><author><name sortKey="Mahmud, S M" sort="Mahmud, S M" uniqKey="Mahmud S" first="S M" last="Mahmud">S M Mahmud</name><affiliation><nlm:affiliation>Department of Community Health Sciences,University of Manitoba,Winnipeg, MB,Canada.</nlm:affiliation></affiliation></author></analytic><series><title level="j">Epidemiology and infection</title><idno type="eISSN">1469-4409</idno><imprint><date when="2014" type="published">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Databases, Factual</term><term>Disease Outbreaks</term><term>Emergency Service, Hospital (statistics & numerical data)</term><term>Female</term><term>Humans</term><term>Incidence</term><term>Influenza, Human (diagnosis)</term><term>Influenza, Human (epidemiology)</term><term>Influenza, Human (therapy)</term><term>Internet</term><term>Linear Models</term><term>Male</term><term>Manitoba (epidemiology)</term><term>Population Surveillance (methods)</term><term>Severity of Illness Index</term></keywords><keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Influenza, Human</term><term>Manitoba</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Population Surveillance</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Emergency Service, Hospital</term></keywords><keywords scheme="MESH" qualifier="therapy" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Databases, Factual</term><term>Disease Outbreaks</term><term>Female</term><term>Humans</term><term>Incidence</term><term>Internet</term><term>Linear Models</term><term>Male</term><term>Severity of Illness Index</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">We evaluated syndromic indicators of influenza disease activity developed using emergency department (ED) data - total ED visits attributed to influenza-like illness (ILI) ('ED ILI volume') and percentage of visits attributed to ILI ('ED ILI percent') - and Google flu trends (GFT) data (ILI cases/100 000 physician visits). Congruity and correlation among these indicators and between these indicators and weekly count of laboratory-confirmed influenza in Manitoba was assessed graphically using linear regression models. Both ED and GFT data performed well as syndromic indicators of influenza activity, and were highly correlated with each other in real time. The strongest correlations between virological data and ED ILI volume and ED ILI percent, respectively, were 0·77 and 0·71. The strongest correlation of GFT was 0·74. Seasonal influenza activity may be effectively monitored using ED and GFT data.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">24480399</PMID><DateCompleted><Year>2014</Year><Month>11</Month><Day>26</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>02</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1469-4409</ISSN><JournalIssue CitedMedium="Internet"><Volume>142</Volume><Issue>11</Issue><PubDate><Year>2014</Year><Month>Nov</Month></PubDate></JournalIssue><Title>Epidemiology and infection</Title><ISOAbbreviation>Epidemiol. Infect.</ISOAbbreviation></Journal><ArticleTitle>Emergency department and 'Google flu trends' data as syndromic surveillance indicators for seasonal influenza.</ArticleTitle><Pagination><MedlinePgn>2397-405</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1017/S0950268813003464</ELocationID><Abstract><AbstractText>We evaluated syndromic indicators of influenza disease activity developed using emergency department (ED) data - total ED visits attributed to influenza-like illness (ILI) ('ED ILI volume') and percentage of visits attributed to ILI ('ED ILI percent') - and Google flu trends (GFT) data (ILI cases/100 000 physician visits). Congruity and correlation among these indicators and between these indicators and weekly count of laboratory-confirmed influenza in Manitoba was assessed graphically using linear regression models. Both ED and GFT data performed well as syndromic indicators of influenza activity, and were highly correlated with each other in real time. The strongest correlations between virological data and ED ILI volume and ED ILI percent, respectively, were 0·77 and 0·71. The strongest correlation of GFT was 0·74. Seasonal influenza activity may be effectively monitored using ED and GFT data.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Thompson</LastName><ForeName>L H</ForeName><Initials>LH</Initials><AffiliationInfo><Affiliation>Department of Community Health Sciences,University of Manitoba,Winnipeg, MB,Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Malik</LastName><ForeName>M T</ForeName><Initials>MT</Initials><AffiliationInfo><Affiliation>Department of Community Health Sciences,University of Manitoba,Winnipeg, MB,Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gumel</LastName><ForeName>A</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Department of Mathematics,University of Manitoba,Winnipeg, MB,Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Strome</LastName><ForeName>T</ForeName><Initials>T</Initials><AffiliationInfo><Affiliation>Department of Emergency Medicine,University of Manitoba,Winnipeg, MB,Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Mahmud</LastName><ForeName>S M</ForeName><Initials>SM</Initials><AffiliationInfo><Affiliation>Department of Community Health Sciences,University of Manitoba,Winnipeg, MB,Canada.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D003160">Comparative Study</PublicationType><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2014</Year><Month>01</Month><Day>20</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="D016208" MajorTopicYN="N">Databases, Factual</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004196" MajorTopicYN="Y">Disease Outbreaks</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004636" MajorTopicYN="N">Emergency Service, Hospital</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</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="Q000175" MajorTopicYN="N">diagnosis</QualifierName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000628" MajorTopicYN="N">therapy</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D020407" MajorTopicYN="Y">Internet</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D016014" MajorTopicYN="N">Linear Models</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008350" MajorTopicYN="N">Manitoba</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011159" MajorTopicYN="N">Population Surveillance</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D012720" MajorTopicYN="N">Severity of Illness Index</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2014</Year><Month>2</Month><Day>1</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2014</Year><Month>2</Month><Day>1</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2014</Year><Month>12</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">24480399</ArticleId><ArticleId IdType="pii">S0950268813003464</ArticleId><ArticleId IdType="doi">10.1017/S0950268813003464</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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