Article: Estimating infection attack rates and severity in real time during an influenza pandemic: Analysis of serial cross-sectional serologic surveillance data
| Title | Estimating infection attack rates and severity in real time during an influenza pandemic: Analysis of serial cross-sectional serologic surveillance data | ||||||||||||||
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| Authors | Wu, JT2 Ho, A2 Ma, ESK2 Lee, CK1 Chu, DKW2 Ho, PL2 Hung, IFN2 Ho, LM2 Lin, CK1 Tsang, T5 Lo, SV1 3 Lau, YL2 Leung, GM3 Cowling, BJ2 Peiris, JSM2 4 | ||||||||||||||
| Keywords | 2009 h1n1 influenza Controlled study Cross-sectional study Disease transmission Epidemic | ||||||||||||||
| Issue Date | 2011 | ||||||||||||||
| Publisher | Public 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?] DOI: http://dx.doi.org/10.1371/journal.pmed.1001103 | ||||||||||||||
| 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. | ||||||||||||||
| ISSN | 1549-1277 2011 Impact Factor: 16.269 2011 SCImago Journal Rankings: 1.041 | ||||||||||||||
| DOI | http://dx.doi.org/10.1371/journal.pmed.1001103 | ||||||||||||||
| ISI Accession Number ID | WOS:000296552400004
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. | ||||||||||||||
| PubMed Central ID | PMC3186812 | ||||||||||||||
| References | References in Scopus | ||||||||||||||
| Grants | A 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 Control of Pandemic and Inter-pandemic Influenza A 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.contributor.author | Wu, JT | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| dc.contributor.author | Ho, A | ||||||||||||||
| dc.contributor.author | Ma, ESK | ||||||||||||||
| dc.contributor.author | Lee, CK | ||||||||||||||
| dc.contributor.author | Chu, DKW | ||||||||||||||
| dc.contributor.author | Ho, PL | ||||||||||||||
| dc.contributor.author | Hung, IFN | ||||||||||||||
| dc.contributor.author | Ho, LM | ||||||||||||||
| dc.contributor.author | Lin, CK | ||||||||||||||
| dc.contributor.author | Tsang, T | ||||||||||||||
| dc.contributor.author | Lo, SV | ||||||||||||||
| dc.contributor.author | Lau, YL | ||||||||||||||
| dc.contributor.author | Leung, GM | ||||||||||||||
| dc.contributor.author | Cowling, BJ | ||||||||||||||
| dc.contributor.author | Peiris, JSM | ||||||||||||||
| dc.date.accessioned | 2011-12-21T08:54:15Z | ||||||||||||||
| dc.date.available | 2011-12-21T08:54:15Z | ||||||||||||||
| dc.date.issued | 2011 | ||||||||||||||
| dc.description.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. | ||||||||||||||
| dc.description.grant | A 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.description.grant | Control of Pandemic and Inter-pandemic Influenza | ||||||||||||||
| dc.description.grant | A 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.description.grantcode | 101662 | ||||||||||||||
| dc.description.grantcode | 97655 | ||||||||||||||
| dc.description.grantcode | 100759 | ||||||||||||||
| dc.description.nature | published_or_final_version | ||||||||||||||
| dc.identifier.citation | Plos Medicine, 2011, v. 8 n. 10 [How to Cite?] DOI: http://dx.doi.org/10.1371/journal.pmed.1001103 | ||||||||||||||
| dc.identifier.citeulike | 9885685 | ||||||||||||||
| dc.identifier.doi | http://dx.doi.org/10.1371/journal.pmed.1001103 | ||||||||||||||
| dc.identifier.epage | 11 | ||||||||||||||
| dc.identifier.hkuros | 198000 | ||||||||||||||
| dc.identifier.isi | WOS:000296552400004
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. | ||||||||||||||
| dc.identifier.issn | 1549-1277 2011 Impact Factor: 16.269 2011 SCImago Journal Rankings: 1.041 | ||||||||||||||
| dc.identifier.issue | 10 | ||||||||||||||
| dc.identifier.pmcid | PMC3186812 | ||||||||||||||
| dc.identifier.pmid | 21990967 | ||||||||||||||
| dc.identifier.scopus | eid_2-s2.0-80055051035 | ||||||||||||||
| dc.identifier.spage | 1 | ||||||||||||||
| dc.identifier.uri | http://hdl.handle.net/10722/143768 | ||||||||||||||
| dc.identifier.volume | 8 | ||||||||||||||
| dc.language | eng | ||||||||||||||
| dc.publisher | Public Library of Science. The Journal's web site is located at http://medicine.plosjournals.org/perlserv/?request=index-html&issn=1549-1676 | ||||||||||||||
| dc.publisher.place | United States | ||||||||||||||
| dc.relation.ispartof | PLoS Medicine | ||||||||||||||
| dc.relation.references | References in Scopus | ||||||||||||||
| dc.rights | Creative Commons: Attribution 3.0 Hong Kong License | ||||||||||||||
| dc.subject | 2009 h1n1 influenza | ||||||||||||||
| dc.subject | Controlled study | ||||||||||||||
| dc.subject | Cross-sectional study | ||||||||||||||
| dc.subject | Disease transmission | ||||||||||||||
| dc.subject | Epidemic | ||||||||||||||
| dc.title | Estimating infection attack rates and severity in real time during an influenza pandemic: Analysis of serial cross-sectional serologic surveillance data | ||||||||||||||
| dc.type | Article |
Author Affiliations
- Hong Kong Hospital Authority
- The University of Hong Kong Li Ka Shing Faculty of Medicine
- Food and Health Bureau
- HKU-Pasteur Research Centre
- Centre for Health Protection