Estimating Infection Attack Rates and Severity in Real Time during an Influenza Pandemic: Analysis of Serial Cross-Sectional Serologic Surveillance Data.

Joseph T Wu (1) , Andrew Ho (1) , Edward S K Ma (2) , Cheuk Kwong Lee (3) , Daniel K W Chu (2) , Po-Lai Ho (2) , Ivan F N Hung (4) , Lai Ming Ho (1) , Che Kit Lin (3) , Thomas Tsang (5) , Su-Vui Lo (6, 7) , Yu-Lung Lau (8) , Gabriel M Leung (7) , Benjamin J Cowling (1) , J S Malik Peiris (2, 9)

1 Department of Community Medicine and School of Public Health
2 Department of Microbiology [HKU]
3 Hong Kong Red Cross Blood Transfusion Service
4 Department of Medicine
5 Centre for Health Protection
6 Hospital Authority
7 Food and Health Bureau
8 Department of Paediatrics and Adolescent Medicine [HKU]
9 Centre de recherche Université de Hong-Kong-Pasteur

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.

Domaines: Virologie

Joseph T Wu, Andrew Ho, Edward S K Ma, Cheuk Kwong Lee, Daniel K W Chu, et al.. Estimating Infection Attack Rates and Severity in Real Time during an Influenza Pandemic: Analysis of Serial Cross-Sectional Serologic Surveillance Data.. PLoS Medicine, 2011, 8 (10), pp.e1001103. ⟨10.1371/journal.pmed.1001103⟩. ⟨pasteur-00639818⟩