Dataset Information

Estimating influenza disease burden from population-based surveillance data in the United States.

ABSTRACT: Annual estimates of the influenza disease burden provide information to evaluate programs and allocate resources. We used a multiplier method with routine population-based surveillance data on influenza hospitalization in the United States to correct for under-reporting and estimate the burden of influenza for seasons after the 2009 pandemic. Five sites of the Influenza Hospitalization Surveillance Network (FluSurv-NET) collected data on the frequency and sensitivity of influenza testing during two seasons to estimate under-detection. Population-based rates of influenza-associated hospitalization and Intensive Care Unit admission from 2010-2013 were extrapolated to the U.S. population from FluSurv-NET and corrected for under-detection. Influenza deaths were calculated using a ratio of deaths to hospitalizations. We estimated that influenza-related hospitalizations were under-detected during 2010-11 by a factor of 2.1 (95%CI 1.7-2.9) for age < 18 years, 3.1 (2.4-4.5) for ages 18-64 years, and 5.2 (95%CI 3.8-8.3) for age 65+. Results were similar in 2011-12. Extrapolated estimates for 3 seasons from 2010-2013 included: 114,192-624,435 hospitalizations, 18,491-95,390 ICU admissions, and 4,915-27,174 deaths per year; 54-70% of hospitalizations and 71-85% of deaths occurred among adults aged 65+. Influenza causes a substantial disease burden in the U.S. that varies by age and season. Periodic estimation of multipliers across multiple sites and age groups improves our understanding of influenza detection in sentinel surveillance systems. Adjusting surveillance data using a multiplier method is a relatively simple means to estimate the impact of influenza and the subsequent value of interventions to prevent influenza.

SUBMITTER: Reed C

PROVIDER: S-EPMC4349859 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Estimating influenza disease burden from population-based surveillance data in the United States.

Reed Carrie C Chaves Sandra S SS Daily Kirley Pam P Emerson Ruth R Aragon Deborah D Hancock Emily B EB Butler Lisa L Baumbach Joan J Hollick Gary G Bennett Nancy M NM Laidler Matthew R MR Thomas Ann A Meltzer Martin I MI Finelli Lyn L

PloS one 20150304 3

Annual estimates of the influenza disease burden provide information to evaluate programs and allocate resources. We used a multiplier method with routine population-based surveillance data on influenza hospitalization in the United States to correct for under-reporting and estimate the burden of influenza for seasons after the 2009 pandemic. Five sites of the Influenza Hospitalization Surveillance Network (FluSurv-NET) collected data on the frequency and sensitivity of influenza testing during ...[more]

PMID: 25738736

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Project description:BACKGROUND:Measures of the contribution of influenza to Streptococcus pneumoniae infections, both in the seasonal and pandemic setting, are needed to predict the burden of secondary bacterial infections in future pandemics to inform stockpiling. The magnitude of the interaction between these two pathogens has been difficult to quantify because both infections are mainly clinically diagnosed based on signs and symptoms; a combined viral-bacterial testing is rarely performed in routine clinical practice; and surveillance data suffer from confounding problems common to all ecological studies. We proposed a novel multivariate model for age-stratified disease incidence, incorporating contact patterns and estimating disease transmission within and across groups. METHODS AND FINDINGS:We used surveillance data from England over the years 2009 to 2017. Influenza infections were identified through the virological testing of samples taken from patients diagnosed with influenza-like illness (ILI) within the sentinel scheme run by the Royal College of General Practitioners (RCGP). Invasive pneumococcal disease (IPD) cases were routinely reported to Public Health England (PHE) by all the microbiology laboratories included in the national surveillance system. IPD counts at week t, conditional on the previous time point t-1, were assumed to be negative binomially distributed. Influenza counts were linearly included in the model for the mean IPD counts along with an endemic component describing some seasonal background and an autoregressive component mimicking pneumococcal transmission. Using age-specific counts, Akaike information criterion (AIC)-based model selection suggested that the best fit was obtained when the endemic component was expressed as a function of observed temperature and rainfall. Pneumococcal transmission within the same age group was estimated to explain 33.0% (confidence interval [CI] 24.9%-39.9%) of new cases in the elderly, whereas 50.7% (CI 38.8%-63.2%) of incidence in adults aged 15-44 years was attributed to transmission from another age group. The contribution of influenza on IPD during the 2009 pandemic also appeared to vary greatly across subgroups, being highest in school-age children and adults (18.3%, CI 9.4%-28.2%, and 6.07%, CI 2.83%-9.76%, respectively). Other viral infections, such as respiratory syncytial virus (RSV) and rhinovirus, also seemed to have an impact on IPD: RSV contributed 1.87% (CI 0.89%-3.08%) to pneumococcal infections in the 65+ group, whereas 2.14% (CI 0.87%-3.57%) of cases in the group of 45- to 64-year-olds were attributed to rhinovirus. The validity of this modelling strategy relies on the assumption that viral surveillance adequately represents the true incidence of influenza in the population, whereas the small numbers of IPD cases observed in the younger age groups led to significant uncertainty around some parameter estimates. CONCLUSIONS:Our estimates suggested that a pandemic wave of influenza A/H1N1 with comparable severity to the 2009 pandemic could have a modest impact on school-age children and adults in terms of IPD and a small to negligible impact on infants and the elderly. The seasonal impact of other viruses such as RSV and rhinovirus was instead more important in the older population groups.

Project description:BackgroundIn the last decade, the number of total knee replacements performed annually in the United States has doubled, with disproportionate increases among younger adults. While total knee replacement is a highly effective treatment for end-stage knee osteoarthritis, total knee replacement recipients can experience persistent pain and severe complications. We are aware of no current estimates of the prevalence of total knee replacement among adults in the U.S.MethodsWe used the Osteoarthritis Policy Model, a validated computer simulation model of knee osteoarthritis, and data on annual total knee replacement utilization to estimate the prevalence of primary and revision total knee replacement among adults fifty years of age or older in the U.S. We combined these prevalence estimates with U.S. Census data to estimate the number of adults in the U.S. currently living with total knee replacement. The annual incidence of total knee replacement was derived from two longitudinal knee osteoarthritis cohorts and ranged from 1.6% to 11.9% in males and from 2.0% to 10.9% in females.ResultsWe estimated that 4.0 million (95% confidence interval [CI]: 3.6 million to 4.4 million) adults in the U.S. currently live with a total knee replacement, representing 4.2% (95% CI: 3.7% to 4.6%) of the population fifty years of age or older. The prevalence was higher among females (4.8%) than among males (3.4%) and increased with age. The lifetime risk of primary total knee replacement from the age of twenty-five years was 7.0% (95% CI: 6.1% to 7.8%) for males and 9.5% (95% CI: 8.5% to 10.5%) for females. Over half of adults in the U.S. diagnosed with knee osteoarthritis will undergo a total knee replacement.ConclusionsAmong older adults in the U.S., total knee replacement is considerably more prevalent than rheumatoid arthritis and nearly as prevalent as congestive heart failure. Nearly 1.5 million of those with a primary total knee replacement are fifty to sixty-nine years old, indicating that a large population is at risk for costly revision surgery as well as possible long-term complications of total knee replacement.

Project description:BackgroundThe aim of this study was to assess the disease burden of the 2009 pandemic influenza A(H1N1) in Greece.Methodology/principal findingsData on influenza-like illness (ILI), collected through cross-sectional nationwide telephone surveys of 1,000 households in Greece repeated for 25 consecutive weeks, were combined with data from H1N1 virologic surveillance to estimate the incidence and the clinical attack rate (CAR) of influenza A(H1N1). Alternative definitions of ILI (cough or sore throat and fever>38°C [ILI-38] or fever 37.1-38°C [ILI-37]) were used to estimate the number of symptomatic infections. The infection attack rate (IAR) was approximated using estimates from published studies on the frequency of fever in infected individuals. Data on H1N1 morbidity and mortality were used to estimate ICU admission and case fatality (CFR) rates. The epidemic peaked on week 48/2009 with approximately 750-1,500 new cases/100,000 population per week, depending on ILI-38 or ILI-37 case definition, respectively. By week 6/2010, 7.1%-15.6% of the population in Greece was estimated to be symptomatically infected with H1N1. Children 5-19 years represented the most affected population group (CAR:27%-54%), whereas individuals older than 64 years were the least affected (CAR:0.6%-2.2%). The IAR (95% CI) of influenza A(H1N1) was estimated to be 19.7% (13.3%, 26.1%). Per 1,000 symptomatic cases, based on ILI-38 case definition, 416 attended health services, 108 visited hospital emergency departments and 15 were admitted to hospitals. ICU admission rate and CFR were 37 and 17.5 per 100,000 symptomatic cases or 13.4 and 6.3 per 100,000 infections, respectively.Conclusions/significanceInfluenza A(H1N1) infected one fifth and caused symptomatic infection in up to 15% of the Greek population. Although individuals older than 65 years were the least affected age group in terms of attack rate, they had 55 and 185 times higher risk of ICU admission and CFR, respectively.

Dataset Information

Estimating influenza disease burden from population-based surveillance data in the United States.

Publications

Estimating influenza disease burden from population-based surveillance data in the United States.

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