Extended abstract: Combining statistical analysis and Markov models with public health data to infer age-specific background mortality rates for hepatitis C infection in the U.S.

Abstract

Chronic hepatitis C (HCV) is a significant public health problem affecting 2.7-3.9 million Americans. Quantifying mortality rates of HCV-infected individuals permits more accurate estimates of the potential benefits of HCV screening and treatment. With 5% of older Americans infected with HCV, cost-effectiveness analyses of expanded HCV screening and treatment require methods to appropriately quantify differential mortality risks. No single study contains data needed to estimate subgroup-specific prevalence of HCV, risk factor status, and mortality risks. We developed a combined modeling approach to infer risk-group-specific mortality rates for chronically HCV-infected U.S. adults. We incorporated estimates from public health data into a Markov model to infer the age-, sex-, race-, risk-, and HCV infection status-specific mortality rates that best fit the overall age-specific population mortality rates. © 2014 Springer International Publishing.