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




Estimating Infection Attack Rates and Severity in Real Time during an Influenza Pandemic: Analysis of Serial Cross-Sectional Serologic Surveillance Data. - Download this document for free, or read online. Document in PDF available to download.

* Corresponding author 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

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.





Author: Joseph T Wu - Andrew Ho - Edward S K Ma - Cheuk Kwong Lee - Daniel K W Chu - Po-Lai Ho - Ivan F N Hung - Lai Ming Ho - Che Kit Li

Source: https://hal.archives-ouvertes.fr/



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