Dataset Information

Estimation of State-Level Prevalence of Hepatitis C Virus Infection, US States and District of Columbia, 2010.

ABSTRACT:

Background.

Hepatitis C virus (HCV) infection is the most common chronic blood-borne infection in the United States and a leading cause of morbidity and mortality. Previous analyses of the US National Health and Nutrition Examination Survey (NHANES) indicated approximately 3.6 million noninstitutionalized persons with antibody to HCV (anti-HCV). However, state-level prevalence remains less understood and cannot be estimated reliably from NHANES alone.

Methods.

We used 3 publicly available government data sources to estimate anti-HCV prevalence in each US state among noninstitutionalized persons aged ?18 years. A small-area estimation model combined indirect standardization of NHANES-based prevalence with logistic regression modeling of mortality data, listing acute or chronic HCV infection as a cause of death, from the National Vital Statistics System during 1999-2012. Model results were combined with US Census population sizes to estimate total number and prevalence of persons with antibody to HCV in 2010.

Results.

National anti-HCV prevalence was 1.67% (95% confidence interval [CI], 1.53-1.90), or 3 911 800 (95% CI, 3 589 400- 4 447 500) adults in 2010. State-specific prevalence ranged from 0.71% (Illinois) to 3.34% (Oklahoma). The West census region had the highest region-specific prevalence (2.14% [95% CI, 1.96-2.48]); 10 of 13 states had rates above the national average. The South had the highest number of persons with anti-HCV (n = 1561600 [95% CI, 1 427 700-1 768 900]). The Midwest had the lowest region-specific prevalence (1.14% [95% CI, 1.04%-1.30%]).

Conclusions.

States in the US West and South have been most impacted by hepatitis C. Estimates of HCV infection burden are essential to guide policy and programs to optimally prevent, detect, and cure infection.

SUBMITTER: Rosenberg ES

PROVIDER: S-EPMC5434341 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Publications

Estimation of State-Level Prevalence of Hepatitis C Virus Infection, US States and District of Columbia, 2010.

Rosenberg Eli S ES Hall Eric W EW Sullivan Patrick S PS Sanchez Travis H TH Workowski Kimberly A KA Ward John W JW Holtzman Deborah D

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 20170601 11

<h4>Background.</h4>Hepatitis C virus (HCV) infection is the most common chronic blood-borne infection in the United States and a leading cause of morbidity and mortality. Previous analyses of the US National Health and Nutrition Examination Survey (NHANES) indicated approximately 3.6 million noninstitutionalized persons with antibody to HCV (anti-HCV). However, state-level prevalence remains less understood and cannot be estimated reliably from NHANES alone.<h4>Methods.</h4>We used 3 publicly a ...[more]

PMID: 28449115

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Project description:Importance:Infection with hepatitis C virus (HCV) is a major cause of morbidity and mortality in the United States, and incidence has increased rapidly in recent years, likely owing to increased injection drug use. Current estimates of prevalence at the state level are needed to guide prevention and care efforts but are not available through existing disease surveillance systems. Objective:To estimate the prevalence of current HCV infection among adults in each US state and the District of Columbia during the years 2013 to 2016. Design, Setting, and Participants:This survey study used a statistical model to allocate nationally representative HCV prevalence from the National Health and Nutrition Examination Survey (NHANES) according to the spatial demographics and distributions of HCV mortality and narcotic overdose mortality in all National Vital Statistics System death records from 1999 to 2016. Additional literature review and analyses estimated state-level HCV infections among populations not included in the National Health and Nutrition Examination Survey sampling frame. Exposures:State, accounting for birth cohort, biological sex, race/ethnicity, federal poverty level, and year. Main Outcomes and Measures:State-level prevalence estimates of current HCV RNA. Results:In this study, the estimated national prevalence of HCV from 2013 to 2016 was 0.84% (95% CI, 0.75%-0.96%) among adults in the noninstitutionalized US population represented in the NHANES sampling frame, corresponding to 2?035?100 (95% CI, 1?803?600-2?318?000) persons with current infection; accounting for populations not included in NHANES, there were 231?600 additional persons with HCV, adjusting prevalence to 0.93%. Nine states contained 51.9% of all persons living with HCV infection (California [318?900], Texas [202?500], Florida [151?000], New York [116?000], Pennsylvania [93?900], Ohio [89?600], Michigan [69?100], Tennessee [69?100], and North Carolina [66?400]); 5 of these states were in Appalachia. Jurisdiction-level median (range) HCV RNA prevalence was 0.88% (0.45%-2.34%). Of 13 states in the western United States, 10 were above this median. Three of 10 states with the highest HCV prevalence were in Appalachia. Conclusions and Relevance:Using extensive national survey and vital statistics data from an 18-year period, this study found higher prevalence of HCV in the West and Appalachian states for 2013 to 2016 compared with other areas. These estimates can guide state prevention and treatment efforts.

Project description:BackgroundModel-based small area estimation methods can help generate parameter estimates at the district level, where planned population survey sample sizes are not large enough to support direct estimates of HIV prevalence with adequate precision. We computed district-level HIV prevalence estimates and their 95% confidence intervals for districts in Uganda.MethodsOur analysis used direct survey and model-based estimation methods, including Fay-Herriot (area-level) and Battese-Harter-Fuller (unit-level) small area models. We used regression analysis to assess for consistency in estimating HIV prevalence. We use a ratio analysis of the mean square error and the coefficient of variation of the estimates to evaluate precision. The models were applied to Uganda Population-Based HIV Impact Assessment 2016/2017 data with auxiliary information from the 2016 Lot Quality Assurance Sampling survey and antenatal care data from district health information system datasets for unit-level and area-level models, respectively.ResultsEstimates from the model-based and the direct survey methods were similar. However, direct survey estimates were unstable compared with the model-based estimates. Area-level model estimates were more stable than unit-level model estimates. The correlation between unit-level and direct survey estimates was (β1 = 0.66, r2 = 0.862), and correlation between area-level model and direct survey estimates was (β1 = 0.44, r2 = 0.698). The error associated with the estimates decreased by 37.5% and 33.1% for the unit-level and area-level models, respectively, compared to the direct survey estimates.ConclusionsAlthough the unit-level model estimates were less precise than the area-level model estimates, they were highly correlated with the direct survey estimates and had less standard error associated with estimates than the area-level model. Unit-level models provide more accurate and reliable data to support local decision-making when unit-level auxiliary information is available.

Dataset Information

Estimation of State-Level Prevalence of Hepatitis C Virus Infection, US States and District of Columbia, 2010.

Background.

Methods.

Results.

Conclusions.

Publications

Estimation of State-Level Prevalence of Hepatitis C Virus Infection, US States and District of Columbia, 2010.

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