Dataset Information

Estimating influenza attack rates in the United States using a participatory cohort.

ABSTRACT: We considered how participatory syndromic surveillance data can be used to estimate influenza attack rates during the 2012-2013 and 2013-2014 seasons in the United States. Our inference is based on assessing the difference in the rates of self-reported influenza-like illness (ILI, defined as presence of fever and cough/sore throat) among the survey participants during periods of active vs. low influenza circulation as well as estimating the probability of self-reported ILI for influenza cases. Here, we combined Flu Near You data with additional sources (Hong Kong household studies of symptoms of influenza cases and the U.S. Centers for Disease Control and Prevention estimates of vaccine coverage and effectiveness) to estimate influenza attack rates. The estimated influenza attack rate for the early vaccinated Flu Near You members (vaccination reported by week 45) aged 20-64 between calendar weeks 47-12 was 14.7%(95% CI(5.9%,24.1%)) for the 2012-2013 season and 3.6%(-3.3%,10.3%) for the 2013-2014 season. The corresponding rates for the US population aged 20-64 were 30.5% (4.4%, 49.3%) in 2012-2013 and 7.1%(-5.1%, 32.5%) in 2013-2014. The attack rates in women and men were similar each season. Our findings demonstrate that participatory syndromic surveillance data can be used to gauge influenza attack rates during future influenza seasons.

SUBMITTER: Chunara R

PROVIDER: S-EPMC4894435 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Estimating influenza attack rates in the United States using a participatory cohort.

Chunara Rumi R Goldstein Edward E Patterson-Lomba Oscar O Brownstein John S JS

Scientific reports 20150402

We considered how participatory syndromic surveillance data can be used to estimate influenza attack rates during the 2012-2013 and 2013-2014 seasons in the United States. Our inference is based on assessing the difference in the rates of self-reported influenza-like illness (ILI, defined as presence of fever and cough/sore throat) among the survey participants during periods of active vs. low influenza circulation as well as estimating the probability of self-reported ILI for influenza cases. H ...[more]

PMID: 25835538

Similar Datasets

Project description: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.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%.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.

Project description:BackgroundThis study estimated the proportions and numbers of heterosexuals in the United States (U.S.) to calculate rates of heterosexually acquired human immunodeficiency virus (HIV) infection. Quantifying the burden of disease can inform effective prevention planning and resource allocation.MethodsHeterosexuals were defined as males and females who ever had sex with an opposite-sex partner and excluded those with other HIV risks: persons who ever injected drugs and males who ever had sex with another man. We conducted meta-analysis using data from 3 national probability surveys that measured lifetime (ever) sexual activity and injection drug use among persons aged 15 years and older to estimate the proportion of heterosexuals in the United States population. We then applied the proportion of heterosexual persons to census data to produce population size estimates. National HIV infection rates among heterosexuals were calculated using surveillance data (cases attributable to heterosexual contact) in the numerators and the heterosexual population size estimates in the denominators.ResultsAdult and adolescent heterosexuals comprised an estimated 86.7% (95% confidence interval: 84.1%-89.3%) of the U.S. population. The estimate for males was 84.1% (CI: 81.2%-86.9%) and for females was 89.4% (95% CI: 86.9%-91.8%). The HIV diagnosis rate for 2013 was 5.2 per 100,000 heterosexuals and the rate of persons living with diagnosed HIV infection in 2012 was 104 per 100,000 heterosexuals aged 13 years or older. Rates of HIV infection were >20 times as high among black heterosexuals compared to white heterosexuals, indicating considerable disparity. Rates among heterosexual men demonstrated higher disparities than overall population rates for men.ConclusionsThe best available data must be used to guide decision-making for HIV prevention. HIV rates among heterosexuals in the U.S. are important additions to cost effectiveness and other data used to make critical decisions about resources for prevention of HIV infection.

Dataset Information

Estimating influenza attack rates in the United States using a participatory cohort.

Publications

Estimating influenza attack rates in the United States using a participatory cohort.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets