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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.

机译:扩展摘要:将统计分析和Markov模型与公共卫生数据相结合,以推断美国丙型肝炎感染的特定年龄背景死亡率。

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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.
机译:慢性丙型肝炎(HCV)是一个严重的公共卫生问题,影响了2.7-390万美国人。量化HCV感染者的死亡率可以更准确地估计HCV筛查和治疗的潜在益处。由于5%的老年人感染了HCV,扩大HCV筛查和治疗的成本效益分析需要适当量化差异性死亡风险的方法。没有一项单独的研究包含估计亚组HCV患病率,危险因素状态和死亡风险所需的数据。我们开发了一种组合建模方法来推断慢性HCV感染的美国成年人的特定风险组死亡率。我们将公共卫生数据的估计值纳入马尔可夫模型,以推断最适合总体特定年龄人群死亡率的特定年龄,性别,种族,风险和HCV感染状态死亡率。

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