Dataset Information

Real-time estimation of the hospitalization fatality risk of influenza A(H1N1)pdm09 in Hong Kong.

ABSTRACT: During the early stage of an epidemic, timely and reliable estimation of the severity of infections are important for predicting the impact that the influenza viruses will have in the population. We obtained age-specific deaths and hospitalizations for patients with laboratory-confirmed H1N1pdm09 infections from June 2009 to December 2009 in Hong Kong. We retrospectively obtained the real-time estimates of the hospitalization fatality risk (HFR), using crude estimation or allowing for right-censoring for final status in some patients. Models accounting for right-censoring performed better than models without adjustments. The risk of deaths in hospitalized patients with confirmed H1N1pdm09 increased with age. Reliable estimates of the HFR could be obtained before the peak of the first wave of H1N1pdm09 in young and middle-aged adults but after the peak in the elderly. In the next influenza pandemic, timely estimation of the HFR will contribute to risk assessment and disease control.

SUBMITTER: Wong JY

PROVIDER: S-EPMC5528870 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Real-time estimation of the hospitalization fatality risk of influenza A(H1N1)pdm09 in Hong Kong.

Wong J Y JY Wu P P Lau E H Y EH Tsang T K TK Fang V J VJ Ho L-M LM Cowling B J BJ

Epidemiology and infection 20160601 8

During the early stage of an epidemic, timely and reliable estimation of the severity of infections are important for predicting the impact that the influenza viruses will have in the population. We obtained age-specific deaths and hospitalizations for patients with laboratory-confirmed H1N1pdm09 infections from June 2009 to December 2009 in Hong Kong. We retrospectively obtained the real-time estimates of the hospitalization fatality risk (HFR), using crude estimation or allowing for right-cens ...[more]

PMID: 27125572

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Project description:BackgroundWhen an outbreak of a novel pathogen occurs, some of the most pressing questions from a public-health point of view relate to its transmissibility, and the probabilities of different clinical outcomes following infection, to allow an informed response. Estimates of these quantities are often based on household data due to the high potential for transmission in this setting, but typically a rich spectrum of individual-level outcomes (from uninfected to serious illness) are simplified to binary data (infected or not). We address the added benefit from retaining the heterogeneous outcome information in the case of the 2009-10 influenza pandemic, which posed particular problems for estimation of key epidemiological characteristics due to its relatively mild nature and hence low case ascertainment rates.MethodsWe use mathematical models of within-household transmission and case ascertainment, together with Bayesian statistics to estimate transmission probabilities stratified by household size, the variability of infectiousness of cases, and a set of probabilities describing case ascertainment. This novel approach was applied to data we collected from the early "containment phase" stage of the epidemic in Birmingham, England. We also conducted a comprehensive review of studies of household transmission of influenza A(H1N1)pdm09.ResultsWe find large variability in the published estimates of within-household transmissibility of influenza A(H1N1)pdm09 in both model-based studies and those reporting secondary attack rates, finding that these estimates are very sensitive to how an infected case is defined. In particular, we find that reliance on laboratory confirmation alone underestimates the true number of cases, while utilising the heterogeneous range of outcomes (based on case definitions) for household infections allows a far more comprehensive pattern of transmission to be elucidated.ConclusionsDifferences in household sizes and how cases are defined could account for an appreciable proportion of the reported variability of within-household transmissibility of influenza A(H1N1)pdm09. Retaining and statistically analysing the full spectrum of individual-level outcomes (based on case definitions) rather than taking a potentially arbitrary threshold for infection, provides much-needed additional information. In a future pandemic, our approach could be used as a real-time analysis tool to infer the true number of cases, within-household transmission rates and levels of case ascertainment.

Project description:BACKGROUND:Serial cross-sectional data on antibody levels to the 2009 pandemic H1N1 influenza A virus from a population can be used to estimate the infection attack rates and immunity against future infection in the community. METHODS:From April through December 2009, we obtained 12,217 serum specimens from blood donors (aged 16-59 years), 2520 specimens from hospital outpatients (aged 5-59 years), and 917 specimens from subjects involved in a community pediatric cohort study (aged 5-14 years). We estimated infection attack rates by comparing the proportions of specimens with antibody titers ? 1:40 by viral microneutralization before and after the first wave of the pandemic. Estimates were validated using paired serum samples from 324 individuals that spanned the first wave. Combining these estimates with epidemiologic surveillance data, we calculated the proportion of infections that led to hospitalization, admission to the intensive care unit (ICU), and death. RESULTS:We found that 3.3% and 14% of persons aged 5-59 years had antibody titers ? 1:40 before and after the first wave, respectively. The overall attack rate was 10.7%, with age stratification as follows: 43.4% in persons aged 5-14 years, 15.8% in persons aged 15-19 years, 11.8% in persons aged 20-29 years, and 4%-4.6% in persons aged 30-59 years. Case-hospitalization rates were 0.47%-0.87% among persons aged 5-59 years. Case-ICU rates were 7.9 cases per 100,000 infections in persons aged 5-14 years and 75 cases per 100,000 infections in persons aged 50-59 years, respectively. Case-fatality rates were 0.4 cases per 100,000 infections in persons aged 5-14 years and 26.5 cases per 100,000 infections in persons aged 50-59 years, respectively. CONCLUSIONS:Almost half of all school-aged children in Hong Kong were infected during the first wave. Compared with school children aged 5-14 years, older adults aged 50-59 years had 9.5 and 66 times higher risks of ICU admission and death if infected, respectively.

Dataset Information

Real-time estimation of the hospitalization fatality risk of influenza A(H1N1)pdm09 in Hong Kong.

Publications

Real-time estimation of the hospitalization fatality risk of influenza A(H1N1)pdm09 in Hong Kong.

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