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

Wu, Joseph T.; Ho, Andrew Fu Wah; Edward, S. K.; Lee, Cheuk Kwong; Chu, Daniel K.W.; Ho, Po‐Lai; Hung, Ivan Fan-Ngai; Ho, Lok Sang; Lin, Che Kit; Tsang, Thomas; Lo, Su‐Vui; Lau, Yu‐Lung; Leung, Gabriel M.; Cowling, Benjamin J.; Peiris, Malik

doi:10.1371/journal.pmed.1001103

Cited by 61 publications

(103 citation statements)

References 30 publications

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“…We applied the method to estimate the cumulative incidence of H1N1pdm09 virus infection across the entire first epidemic wave in Hong Kong which spanned from April 2009 through to November 2010. While our estimate for the cumulative incidence of H1N1pdm09 virus infection in children was similar to that in other studies, the estimate for adults and elderly were higher than in other studies [7,16,18]. One potential explanation for this observation is that our data were from a vaccine trial that involved families of school-age children, and therefore excluded adults that did not live with children and might therefore generally be at lower risk of infection [31].…”

Section: Discussionsupporting

confidence: 77%

Interpreting Seroepidemiologic Studies of Influenza in a Context of Nonbracketing Sera

et al. 2016

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Background In influenza epidemiology, analysis of paired sera collected from people before and after influenza seasons has been used for decades to study the cumulative incidence of influenza virus infections in populations. However, interpretation becomes challenging when sera are collected after the start or before the end of an epidemic, and do not neatly bracket the epidemic. Methods Serum samples were collected longitudinally in a community-based study. Most participants provided their first serum after the start of circulation of influenza A(H1N1)pdm09 virus in 2009. We developed a Bayesian hierarchical model to correct for non-bracketing sera and estimate the cumulative incidence of infection from the serological data and surveillance data in Hong Kong. Results We analysed 4843 sera from 2097 unvaccinated participants in the study, collected from April 2009 through December 2010. After accounting for non-bracketing, we estimated that the cumulative incidence of H1N1pdm09 virus infection was 45.1% (95% credible interval, CI: 40.2%, 49.2%), 16.5% (95% CI: 13.0%, 19.7%) and 11.3% (95% CI: 5.9%, 17.5%) for children 0–18y, adults 19–50y and older adults >50y respectively. Including all available data substantially increased precision compared to a simpler analysis based only on sera collected at 6-month intervals in a subset of participants. Conclusions We developed a framework for the analysis of antibody titers that accounted for the timing of sera collection with respect to influenza activity and permitted robust estimation of the cumulative incidence of infection during an epidemic.

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Section: Discussionsupporting

confidence: 77%

Interpreting Seroepidemiologic Studies of Influenza in a Context of Nonbracketing Sera

et al. 2016

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“…We have previously discussed real-time estimation of the cumulative incidence of infection based on serologic data. 73 This would form the denominator of the infection fatality risk, but, as noted previously, this is unlikely to be available early in the pandemic.…”

Section: Discussionmentioning

confidence: 99%

Case Fatality Risk of Influenza A (H1N1pdm09)

et al. 2013

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Background During the 2009 influenza pandemic, uncertainty surrounding the seriousness of human infections with the H1N1pdm09 virus hindered appropriate public health response. One measure of seriousness is the case fatality risk, defined as the probability of mortality among people classified as cases. Methods We conducted a systematic review to summarize published estimates of the case fatality risk of the pandemic influenza H1N1pdm09 virus. Only studies that reported population-based estimates were included. Results We included 77 estimates of the case fatality risk from 50 published studies, about one-third of which were published within the first 9 months of the pandemic. We identified very substantial heterogeneity in published estimates, ranging from less than 1 to more than 10,000 deaths per 100,000 cases or infections. The choice of case definition in the denominator accounted for substantial heterogeneity, with the higher estimates based on laboratory-confirmed cases (point estimates= 0–13,500 per 100,000 cases) compared with symptomatic cases (point estimates= 0–1,200 per 100,000 cases) or infections (point estimates=1–10 per 100,000 infections). Risk based on symptomatic cases increased substantially with age. Conclusions Our review highlights the difficulty in estimating the seriousness of infection with a novel influenza virus using the case fatality risk. In addition, substantial variability in age-specific estimates complicates the interpretation of the overall case fatality risk and comparisons among populations. A consensus is needed on how to define and measure the seriousness of infection before the next pandemic.

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“…Along with population‐level surveillance to capture numerators (i.e., H1N1pdm, hospitalizations and deaths), representative serological studies are designed to collect denominator data (i.e., infections) that can be used to estimate severity parameters such as the CFR (i.e., the total number of H1N1pdm deaths divided by the total number of H1N1pdm infections) and hospitalization ratios (number of H1N1pdm hospitalizations divided by H1N1pdm infections). Thus, analysis of serological data can provide accurate measures of incidence, reduce the uncertainty around severity assessment, and help inform the appropriate intensity and targeting of mitigation policies 8, 9, 10…”

Section: Introductionmentioning

confidence: 99%

Estimating age‐specific cumulative incidence for the 2009 influenza pandemic: a meta‐analysis of A(H1N1)pdm09 serological studies from 19 countries

Kerkhove¹,

Hirve

Koukounari

et al. 2013

Influenza Resp Viruses

164

139

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BackgroundThe global impact of the 2009 influenza A(H1N1) pandemic (H1N1pdm) is not well understood.ObjectivesWe estimate overall and age‐specific prevalence of cross‐reactive antibodies to H1N1pdm virus and rates of H1N1pdm infection during the first year of the pandemic using data from published and unpublished H1N1pdm seroepidemiological studies.MethodsPrimary aggregate H1N1pdm serologic data from each study were stratified in standardized age groups and evaluated based on when sera were collected in relation to national or subnational peak H1N1pdm activity. Seropositivity was assessed using well‐described and standardized hemagglutination inhibition (HI titers ≥32 or ≥40) and microneutralization (MN ≥ 40) laboratory assays. The prevalence of cross‐reactive antibodies to the H1N1pdm virus was estimated for studies using sera collected prior to the start of the pandemic (between 2004 and April 2009); H1N1pdm cumulative incidence was estimated for studies in which collected both pre‐ and post‐pandemic sera; and H1N1pdm seropositivity was calculated from studies with post‐pandemic sera only (collected between December 2009–June 2010).ResultsData from 27 published/unpublished studies from 19 countries/administrative regions – Australia, Canada, China, Finland, France, Germany, Hong Kong SAR, India, Iran, Italy, Japan, Netherlands, New Zealand, Norway, Reunion Island, Singapore, United Kingdom, United States, and Vietnam – were eligible for inclusion. The overall age‐standardized pre‐pandemic prevalence of cross‐reactive antibodies was 5% (95%CI 3–7%) and varied significantly by age with the highest rates among persons ≥65 years old (14% 95%CI 8–24%). Overall age‐standardized H1N1pdm cumulative incidence was 24% (95%CI 20–27%) and varied significantly by age with the highest in children 5–19 (47% 95%CI 39–55%) and 0–4 years old (36% 95%CI 30–43%).ConclusionsOur results offer unique insight into the global impact of the H1N1 pandemic and highlight the need for standardization of seroepidemiological studies and for their inclusion in pre‐pandemic preparedness plans. Our results taken together with recent global pandemic respiratory‐associated mortality estimates suggest that the case fatality ratio of the pandemic virus was approximately 0·02%.

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

Abstract: This study reports that using serological data coupled with clinical surveillance data can provide real-time estimates of the infection attack rates and severity in an emerging influenza pandemic.

Cited by 61 publications

References 30 publications

Interpreting Seroepidemiologic Studies of Influenza in a Context of Nonbracketing Sera

Interpreting Seroepidemiologic Studies of Influenza in a Context of Nonbracketing Sera

Case Fatality Risk of Influenza A (H1N1pdm09)

Estimating age‐specific cumulative incidence for the 2009 influenza pandemic: a meta‐analysis of A(H1N1)pdm09 serological studies from 19 countries

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