Estimating infection attack rates and severity in real time during an influenza pandemic: analysis of serial cross-sectional serologic surveillance data.
Identifieur interne : 000F97 ( PubMed/Checkpoint ); précédent : 000F96; suivant : 000F98Estimating infection attack rates and severity in real time during an influenza pandemic: analysis of serial cross-sectional serologic surveillance data.
Auteurs : Joseph T. Wu [République populaire de Chine] ; Andrew Ho ; Edward S K. Ma ; Cheuk Kwong Lee ; Daniel K W. Chu ; Po-Lai Ho ; Ivan F N. Hung ; Lai Ming Ho ; Che Kit Lin ; Thomas Tsang ; Su-Vui Lo ; Yu-Lung Lau ; Gabriel M. Leung ; Benjamin J. Cowling ; J S Malik PeirisSource :
- PLoS medicine [ 1549-1676 ] ; 2011.
Descripteurs français
- KwdFr :
- MESH :
- mortalité : Grippe humaine.
- épidémiologie : Grippe humaine.
- Adolescent, Adulte, Adulte d'âge moyen, Enfant, Humains, Pandémies, Santé publique, Sous-type H1N1 du virus de la grippe A, Surveillance de la population, Études séroépidémiologiques, Études transversales.
English descriptors
- KwdEn :
- MESH :
- epidemiology : Influenza, Human.
- methods : Population Surveillance.
- mortality : Influenza, Human.
- Adolescent, Adult, Child, Cross-Sectional Studies, Humans, Influenza A Virus, H1N1 Subtype, Middle Aged, Pandemics, Public Health, Seroepidemiologic Studies.
Abstract
In an emerging influenza pandemic, estimating severity (the probability of a severe outcome, such as hospitalization, if infected) is a public health priority. As many influenza infections are subclinical, sero-surveillance is needed to allow reliable real-time estimates of infection attack rate (IAR) and severity.
DOI: 10.1371/journal.pmed.1001103
PubMed: 21990967
Affiliations:
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pubmed:21990967Le document en format XML
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Wu</name><affiliation wicri:level="1"><nlm:affiliation>Department of Community Medicine and School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China. joewu@hku.hk</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Community Medicine and School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region</wicri:regionArea><wicri:noRegion>Hong Kong Special Administrative Region</wicri:noRegion></affiliation></author><author><name sortKey="Ho, Andrew" sort="Ho, Andrew" uniqKey="Ho A" first="Andrew" last="Ho">Andrew Ho</name></author><author><name sortKey="Ma, Edward S K" sort="Ma, Edward S K" uniqKey="Ma E" first="Edward S K" last="Ma">Edward S K. Ma</name></author><author><name sortKey="Lee, Cheuk Kwong" sort="Lee, Cheuk Kwong" uniqKey="Lee C" first="Cheuk Kwong" last="Lee">Cheuk Kwong Lee</name></author><author><name sortKey="Chu, Daniel K W" sort="Chu, Daniel K W" uniqKey="Chu D" first="Daniel K W" last="Chu">Daniel K W. Chu</name></author><author><name sortKey="Ho, Po Lai" sort="Ho, Po Lai" uniqKey="Ho P" first="Po-Lai" last="Ho">Po-Lai Ho</name></author><author><name sortKey="Hung, Ivan F N" sort="Hung, Ivan F N" uniqKey="Hung I" first="Ivan F N" last="Hung">Ivan F N. Hung</name></author><author><name sortKey="Ho, Lai Ming" sort="Ho, Lai Ming" uniqKey="Ho L" first="Lai Ming" last="Ho">Lai Ming Ho</name></author><author><name sortKey="Lin, Che Kit" sort="Lin, Che Kit" uniqKey="Lin C" first="Che Kit" last="Lin">Che Kit Lin</name></author><author><name sortKey="Tsang, Thomas" sort="Tsang, Thomas" uniqKey="Tsang T" first="Thomas" last="Tsang">Thomas Tsang</name></author><author><name sortKey="Lo, Su Vui" sort="Lo, Su Vui" uniqKey="Lo S" first="Su-Vui" last="Lo">Su-Vui Lo</name></author><author><name sortKey="Lau, Yu Lung" sort="Lau, Yu Lung" uniqKey="Lau Y" first="Yu-Lung" last="Lau">Yu-Lung Lau</name></author><author><name sortKey="Leung, Gabriel M" sort="Leung, Gabriel M" uniqKey="Leung G" first="Gabriel M" last="Leung">Gabriel M. Leung</name></author><author><name sortKey="Cowling, Benjamin J" sort="Cowling, Benjamin J" uniqKey="Cowling B" first="Benjamin J" last="Cowling">Benjamin J. Cowling</name></author><author><name sortKey="Peiris, J S Malik" sort="Peiris, J S Malik" uniqKey="Peiris J" first="J S Malik" last="Peiris">J S Malik Peiris</name></author></analytic><series><title level="j">PLoS medicine</title><idno type="eISSN">1549-1676</idno><imprint><date when="2011" type="published">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adolescent</term><term>Adult</term><term>Child</term><term>Cross-Sectional Studies</term><term>Humans</term><term>Influenza A Virus, H1N1 Subtype</term><term>Influenza, Human (epidemiology)</term><term>Influenza, Human (mortality)</term><term>Middle Aged</term><term>Pandemics</term><term>Population Surveillance (methods)</term><term>Public Health</term><term>Seroepidemiologic Studies</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Adolescent</term><term>Adulte</term><term>Adulte d'âge moyen</term><term>Enfant</term><term>Grippe humaine (mortalité)</term><term>Grippe humaine (épidémiologie)</term><term>Humains</term><term>Pandémies</term><term>Santé publique</term><term>Sous-type H1N1 du virus de la grippe A</term><term>Surveillance de la population ()</term><term>Études séroépidémiologiques</term><term>Études transversales</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Population Surveillance</term></keywords><keywords scheme="MESH" qualifier="mortality" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="mortalité" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adolescent</term><term>Adult</term><term>Child</term><term>Cross-Sectional Studies</term><term>Humans</term><term>Influenza A Virus, H1N1 Subtype</term><term>Middle Aged</term><term>Pandemics</term><term>Public Health</term><term>Seroepidemiologic Studies</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adolescent</term><term>Adulte</term><term>Adulte d'âge moyen</term><term>Enfant</term><term>Humains</term><term>Pandémies</term><term>Santé publique</term><term>Sous-type H1N1 du virus de la grippe A</term><term>Surveillance de la population</term><term>Études séroépidémiologiques</term><term>Études transversales</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In an emerging influenza pandemic, estimating severity (the probability of a severe outcome, such as hospitalization, if infected) is a public health priority. As many influenza infections are subclinical, sero-surveillance is needed to allow reliable real-time estimates of infection attack rate (IAR) and severity.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">21990967</PMID><DateCompleted><Year>2012</Year><Month>02</Month><Day>10</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1549-1676</ISSN><JournalIssue CitedMedium="Internet"><Volume>8</Volume><Issue>10</Issue><PubDate><Year>2011</Year><Month>Oct</Month></PubDate></JournalIssue><Title>PLoS medicine</Title><ISOAbbreviation>PLoS Med.</ISOAbbreviation></Journal><ArticleTitle>Estimating infection attack rates and severity in real time during an influenza pandemic: analysis of serial cross-sectional serologic surveillance data.</ArticleTitle><Pagination><MedlinePgn>e1001103</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pmed.1001103</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">In an emerging influenza pandemic, estimating severity (the probability of a severe outcome, such as hospitalization, if infected) is a public health priority. As many influenza infections are subclinical, sero-surveillance is needed to allow reliable real-time estimates of infection attack rate (IAR) and severity.</AbstractText><AbstractText Label="METHODS AND FINDINGS" NlmCategory="RESULTS">We tested 14,766 sera collected during the first wave of the 2009 pandemic in Hong Kong using viral microneutralization. We estimated IAR and infection-hospitalization probability (IHP) from the serial cross-sectional serologic data and hospitalization data. Had our serologic data been available weekly in real time, we would have obtained reliable IHP estimates 1 wk after, 1-2 wk before, and 3 wk after epidemic peak for individuals aged 5-14 y, 15-29 y, and 30-59 y. The ratio of IAR to pre-existing seroprevalence, which decreased with age, was a major determinant for the timeliness of reliable estimates. If we began sero-surveillance 3 wk after community transmission was confirmed, with 150, 350, and 500 specimens per week for individuals aged 5-14 y, 15-19 y, and 20-29 y, respectively, we would have obtained reliable IHP estimates for these age groups 4 wk before the peak. For 30-59 y olds, even 800 specimens per week would not have generated reliable estimates until the peak because the ratio of IAR to pre-existing seroprevalence for this age group was low. The performance of serial cross-sectional sero-surveillance substantially deteriorates if test specificity is not near 100% or pre-existing seroprevalence is not near zero. These potential limitations could be mitigated by choosing a higher titer cutoff for seropositivity. If the epidemic doubling time is longer than 6 d, then serial cross-sectional sero-surveillance with 300 specimens per week would yield reliable estimates when IAR reaches around 6%-10%.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">Serial cross-sectional serologic data together with clinical surveillance data can allow reliable real-time estimates of IAR and severity in an emerging pandemic. Sero-surveillance for pandemics should be considered.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Wu</LastName><ForeName>Joseph T</ForeName><Initials>JT</Initials><AffiliationInfo><Affiliation>Department of Community Medicine and School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China. joewu@hku.hk</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ho</LastName><ForeName>Andrew</ForeName><Initials>A</Initials></Author><Author ValidYN="Y"><LastName>Ma</LastName><ForeName>Edward S K</ForeName><Initials>ES</Initials></Author><Author ValidYN="Y"><LastName>Lee</LastName><ForeName>Cheuk Kwong</ForeName><Initials>CK</Initials></Author><Author ValidYN="Y"><LastName>Chu</LastName><ForeName>Daniel K W</ForeName><Initials>DK</Initials></Author><Author ValidYN="Y"><LastName>Ho</LastName><ForeName>Po-Lai</ForeName><Initials>PL</Initials></Author><Author ValidYN="Y"><LastName>Hung</LastName><ForeName>Ivan F N</ForeName><Initials>IF</Initials></Author><Author ValidYN="Y"><LastName>Ho</LastName><ForeName>Lai Ming</ForeName><Initials>LM</Initials></Author><Author ValidYN="Y"><LastName>Lin</LastName><ForeName>Che Kit</ForeName><Initials>CK</Initials></Author><Author ValidYN="Y"><LastName>Tsang</LastName><ForeName>Thomas</ForeName><Initials>T</Initials></Author><Author ValidYN="Y"><LastName>Lo</LastName><ForeName>Su-Vui</ForeName><Initials>SV</Initials></Author><Author ValidYN="Y"><LastName>Lau</LastName><ForeName>Yu-Lung</ForeName><Initials>YL</Initials></Author><Author ValidYN="Y"><LastName>Leung</LastName><ForeName>Gabriel M</ForeName><Initials>GM</Initials></Author><Author ValidYN="Y"><LastName>Cowling</LastName><ForeName>Benjamin J</ForeName><Initials>BJ</Initials></Author><Author ValidYN="Y"><LastName>Peiris</LastName><ForeName>J S Malik</ForeName><Initials>JS</Initials></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>U54 GM088558</GrantID><Acronym>GM</Acronym><Agency>NIGMS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>1 U54 GM088558</GrantID><Acronym>GM</Acronym><Agency>NIGMS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>N01AI70005</GrantID><Acronym>AI</Acronym><Agency>NIAID NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>HHSN266200700005C</GrantID><Acronym>AI</Acronym><Agency>NIAID NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>HHSN266200700005C</GrantID><Agency>PHS HHS</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D052061">Research Support, N.I.H., Extramural</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2011</Year><Month>10</Month><Day>04</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS Med</MedlineTA><NlmUniqueID>101231360</NlmUniqueID><ISSNLinking>1549-1277</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002648" MajorTopicYN="N">Child</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D003430" MajorTopicYN="N">Cross-Sectional Studies</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D053118" MajorTopicYN="Y">Influenza A Virus, H1N1 Subtype</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007251" MajorTopicYN="N">Influenza, Human</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000401" MajorTopicYN="N">mortality</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011159" MajorTopicYN="N">Population Surveillance</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011634" MajorTopicYN="N">Public Health</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D016036" MajorTopicYN="N">Seroepidemiologic Studies</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate 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Chu</name><name sortKey="Cowling, Benjamin J" sort="Cowling, Benjamin J" uniqKey="Cowling B" first="Benjamin J" last="Cowling">Benjamin J. Cowling</name><name sortKey="Ho, Andrew" sort="Ho, Andrew" uniqKey="Ho A" first="Andrew" last="Ho">Andrew Ho</name><name sortKey="Ho, Lai Ming" sort="Ho, Lai Ming" uniqKey="Ho L" first="Lai Ming" last="Ho">Lai Ming Ho</name><name sortKey="Ho, Po Lai" sort="Ho, Po Lai" uniqKey="Ho P" first="Po-Lai" last="Ho">Po-Lai Ho</name><name sortKey="Hung, Ivan F N" sort="Hung, Ivan F N" uniqKey="Hung I" first="Ivan F N" last="Hung">Ivan F N. Hung</name><name sortKey="Lau, Yu Lung" sort="Lau, Yu Lung" uniqKey="Lau Y" first="Yu-Lung" last="Lau">Yu-Lung Lau</name><name sortKey="Lee, Cheuk Kwong" sort="Lee, Cheuk Kwong" uniqKey="Lee C" first="Cheuk Kwong" last="Lee">Cheuk Kwong Lee</name><name sortKey="Leung, Gabriel M" sort="Leung, Gabriel M" uniqKey="Leung G" first="Gabriel M" last="Leung">Gabriel M. Leung</name><name sortKey="Lin, Che Kit" sort="Lin, Che Kit" uniqKey="Lin C" first="Che Kit" last="Lin">Che Kit Lin</name><name sortKey="Lo, Su Vui" sort="Lo, Su Vui" uniqKey="Lo S" first="Su-Vui" last="Lo">Su-Vui Lo</name><name sortKey="Ma, Edward S K" sort="Ma, Edward S K" uniqKey="Ma E" first="Edward S K" last="Ma">Edward S K. Ma</name><name sortKey="Peiris, J S Malik" sort="Peiris, J S Malik" uniqKey="Peiris J" first="J S Malik" last="Peiris">J S Malik Peiris</name><name sortKey="Tsang, Thomas" sort="Tsang, Thomas" uniqKey="Tsang T" first="Thomas" last="Tsang">Thomas Tsang</name></noCountry><country name="République populaire de Chine"><noRegion><name sortKey="Wu, Joseph T" sort="Wu, Joseph T" uniqKey="Wu J" first="Joseph T" last="Wu">Joseph T. Wu</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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