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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?
Abstract
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. 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
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

 

Author Affiliations
  1. The University of Hong Kong Li Ka Shing Faculty of Medicine
  2. Hong Kong Hospital Authority
  3. Food and Health Bureau
  4. HKU-Pasteur Research Centre
  5. Centre for Health Protection
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-

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