1. Estimating Infection Attack Rates and Severity in Real Time during an Influenza Pandemic: Analysis of Serial Cross-Sectional Serologic Surveillance Data.
- Author
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Wu, Joseph T., Ho, Andrew, Ma, Edward S. K., Lee, Cheuk Kwong, Chu, Daniel K. W., Po-Lai Ho, Hung, Ivan F. N., Lai Ming Ho, Che Kit Lin, Tsang, Thomas, Su-Vui Lo, Yu-Lung Lau, Leung, Gabriel M., Cowling, Benjamin J., and Peiris, J. S. Malik
- Subjects
H1N1 influenza ,HOSPITAL care ,PUBLIC health ,HEALTH outcome assessment ,CROSS-sectional method - 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 serosurveillance 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. [ABSTRACT FROM AUTHOR]
- Published
- 2011
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