Suppr超能文献

基于模型的慢性丙型肝炎患病率估计框架。

A model-based framework for chronic hepatitis C prevalence estimation.

机构信息

School of Pharmacy, University of Waterloo, Kitchener, ON, Canada.

Department of Mathematics and Statistics, University of Guelph, Guelph, ON, Canada.

出版信息

PLoS One. 2019 Nov 21;14(11):e0225366. doi: 10.1371/journal.pone.0225366. eCollection 2019.

Abstract

Chronic hepatitis C (CHC) continues to be a highly burdensome disease worldwide. The often-asymptomatic nature of early-stage CHC means that the disease often remains undiagnosed, leaving its prevalence highly uncertain. This generates significant uncertainty in the planning of hepatitis C eradication programs to meet WHO targets. The aim of this work is to establish a mathematical framework for the estimation of a geographic locale's CHC prevalence and the proportion of its CHC population that remains undiagnosed. A Bayesian MCMC approach is taken to infer these populations from the observed occurrence of CHC-related events using a recently published natural history model of the disease. Using the Canadian context as a specific example, this study estimates that in 2013, the CHC prevalence rate in Canada was 0.63% (95% CI: 0.53% - 0.72%), with 27.1% (95% CI: 19.3% - 36.1%) of the infected population undiagnosed.

摘要

慢性丙型肝炎(CHC)在全球范围内仍是一种负担沉重的疾病。早期 CHC 通常无症状,这意味着该疾病常常未被诊断,其流行率极不确定。这给为实现世界卫生组织目标而制定的丙型肝炎消除规划带来了重大不确定性。这项工作的目的是建立一个数学框架,用于估计某一地理区域的 CHC 流行率以及其未被诊断的 CHC 人群的比例。使用最近发表的疾病自然史模型,通过观察 CHC 相关事件的发生,采用贝叶斯 MCMC 方法从观察到的数据中推断这些人群。本研究以加拿大为例,估计 2013 年加拿大 CHC 的流行率为 0.63%(95%CI:0.53%-0.72%),其中 27.1%(95%CI:19.3%-36.1%)的感染者未被诊断。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c219/6874092/04d00c510584/pone.0225366.g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验