Links for fulltext
     (May Require Subscription)
Supplementary

Article: Estimating infection attack rates and severity in real time during an influenza pandemic: Analysis of serial cross-sectional serologic surveillance data

TitleEstimating infection attack rates and severity in real time during an influenza pandemic: Analysis of serial cross-sectional serologic surveillance data
Authors
Keywords2009 h1n1 influenza
Controlled study
Cross-sectional study
Disease transmission
Epidemic
Issue Date2011
PublisherPublic Library of Science. The Journal's web site is located at http://medicine.plosjournals.org/perlserv/?request=index-html&issn=1549-1676
Citation
Plos Medicine, 2011, v. 8 n. 10 How to Cite?
AbstractBackground: 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. Methods and Findings: 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%. 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. Please see later in the article for the Editors' Summary. © 2011 Wu et al.
Persistent Identifierhttp://hdl.handle.net/10722/143768
ISSN
2011 Impact Factor: 16.269
2015 SCImago Journal Rankings: 5.667
PubMed Central ID
ISI Accession Number ID
Funding AgencyGrant Number
Food and Health Bureau, Government of the Hong Kong SARPHE-20
10090272
Hong Kong University Grants CommitteeAoE/M-12/06
Harvard Center for Communicable Disease Dynamics from the US National Institutes of Health Models of Infectious Disease1 U54 GM088558
EMPERIE (EU)223498
National Institute of Allergy and Infectious Diseases, NIHHHSN266200700005C
N01-AI-70005
MedImmune Inc.
Funding Information:

This project was supported by the Research Fund for the Control of Infectious Disease, Food and Health Bureau, Government of the Hong Kong SAR (grants PHE-20 and 10090272), the Area of Excellence Scheme of the Hong Kong University Grants Committee (grant AoE/M-12/06), the Harvard Center for Communicable Disease Dynamics from the US National Institutes of Health Models of Infectious Disease Agent Study program (grant 1 U54 GM088558), EMPERIE (EU FP7 grant 223498), and the National Institute of Allergy and Infectious Diseases, NIH (contract HHSN266200700005C; ADB No. N01-AI-70005). The funding bodies had no role in study design, data collection and analysis, preparation of the manuscript, or the decision to publish.

References
Grants

 

DC FieldValueLanguage
dc.contributor.authorWu, JTen_HK
dc.contributor.authorHo, Aen_HK
dc.contributor.authorMa, ESKen_HK
dc.contributor.authorLee, CKen_HK
dc.contributor.authorChu, DKWen_HK
dc.contributor.authorHo, PLen_HK
dc.contributor.authorHung, IFNen_HK
dc.contributor.authorHo, LMen_HK
dc.contributor.authorLin, CKen_HK
dc.contributor.authorTsang, Ten_HK
dc.contributor.authorLo, SVen_HK
dc.contributor.authorLau, YLen_HK
dc.contributor.authorLeung, GMen_HK
dc.contributor.authorCowling, BJen_HK
dc.contributor.authorPeiris, JSMen_HK
dc.date.accessioned2011-12-21T08:54:15Z-
dc.date.available2011-12-21T08:54:15Z-
dc.date.issued2011en_HK
dc.identifier.citationPlos Medicine, 2011, v. 8 n. 10en_HK
dc.identifier.issn1549-1277en_HK
dc.identifier.urihttp://hdl.handle.net/10722/143768-
dc.description.abstractBackground: 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. Methods and Findings: 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%. 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. Please see later in the article for the Editors' Summary. © 2011 Wu et al.en_HK
dc.languageengen_US
dc.publisherPublic Library of Science. The Journal's web site is located at http://medicine.plosjournals.org/perlserv/?request=index-html&issn=1549-1676en_HK
dc.relation.ispartofPLoS Medicineen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subject2009 h1n1 influenza-
dc.subjectControlled study-
dc.subjectCross-sectional study-
dc.subjectDisease transmission-
dc.subjectEpidemic-
dc.titleEstimating infection attack rates and severity in real time during an influenza pandemic: Analysis of serial cross-sectional serologic surveillance dataen_HK
dc.typeArticleen_HK
dc.identifier.emailWu, JT: joewu@hkucc.hku.hken_HK
dc.identifier.emailHung, IFN: ivanhung@hkucc.hku.hken_HK
dc.identifier.emailHo, LM: lmho@hkucc.hku.hken_HK
dc.identifier.emailLau, YL: lauylung@hku.hken_HK
dc.identifier.emailLeung, GM: gmleung@hku.hken_HK
dc.identifier.emailCowling, BJ: bcowling@hku.hken_HK
dc.identifier.emailPeiris, JSM: malik@hkucc.hku.hken_HK
dc.identifier.authorityWu, JT=rp00517en_HK
dc.identifier.authorityHung, IFN=rp00508en_HK
dc.identifier.authorityHo, LM=rp00360en_HK
dc.identifier.authorityLau, YL=rp00361en_HK
dc.identifier.authorityLeung, GM=rp00460en_HK
dc.identifier.authorityCowling, BJ=rp01326en_HK
dc.identifier.authorityPeiris, JSM=rp00410en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1371/journal.pmed.1001103en_HK
dc.identifier.pmid21990967-
dc.identifier.pmcidPMC3186812-
dc.identifier.scopuseid_2-s2.0-80055051035en_HK
dc.identifier.hkuros198000en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80055051035&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume8en_HK
dc.identifier.issue10en_HK
dc.identifier.spage1en_US
dc.identifier.epage11en_US
dc.identifier.isiWOS:000296552400004-
dc.publisher.placeUnited Statesen_HK
dc.relation.projectA longitudinal study of infection attack rates among hospital outpatients in Hong Kong during the epidemic of the human swine influenza A/H1N1 virus in 2009 by tracking temporal changes in age-specific seroprevalence rates-
dc.relation.projectControl of Pandemic and Inter-pandemic Influenza-
dc.relation.projectA detailed longitudinal study of infection attack rates among healthy adults in Hong Kong during the epidemic of the human swine influenza A/H1N1 virus in 2009-
dc.identifier.scopusauthoridWu, JT=7409256423en_HK
dc.identifier.scopusauthoridHo, A=7402675209en_HK
dc.identifier.scopusauthoridMa, ESK=24725277400en_HK
dc.identifier.scopusauthoridLee, CK=54404843400en_HK
dc.identifier.scopusauthoridChu, DKW=7201734326en_HK
dc.identifier.scopusauthoridHo, PL=55276473900en_HK
dc.identifier.scopusauthoridHung, IFN=7006103457en_HK
dc.identifier.scopusauthoridHo, LM=7402955625en_HK
dc.identifier.scopusauthoridLin, CK=54404964900en_HK
dc.identifier.scopusauthoridTsang, T=7101832378en_HK
dc.identifier.scopusauthoridLo, SV=8426498400en_HK
dc.identifier.scopusauthoridLau, YL=7201403380en_HK
dc.identifier.scopusauthoridLeung, GM=7007159841en_HK
dc.identifier.scopusauthoridCowling, BJ=8644765500en_HK
dc.identifier.scopusauthoridPeiris, JSM=7005486823en_HK
dc.identifier.citeulike9885685-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats