SCH: INT: Collaborative Research: Smart Intervention Strategies for Hepatitis C Elimination

SCH：INT：合作研究：消除丙型肝炎的智能干预策略

• 批准号: 1722614
• 负责人: Turgay Ayer
• 金额: $ 43万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2023-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1722614&HistoricalAwards=false
• 关键词: SCH; INT; Collaborative; Research; Smart

Chronic hepatitis C virus (HCV) infection is a global health problem that causes more deaths than other common infectious conditions, including HIV/AIDS, tuberculosis and malaria. Because the infection has a long latency period with few symptons, the majority of those infected remain unaware of their health status. The World Health Organization (WHO) and the National Academy of Medicine recently set an ambitious target to eliminate HCV by 2030; however, several challenges exist. The true prevalence of disease is unknown and effective screening policies do not exist, and treatment, while effective, is very expensive. This project has the following three overarching aims: 1) estimating the true disease burden of hepatitis C at the State and National level; 2) identifying effective screening and treatment strategies for identifying hepatitis C infection; and 3) designing practical decision support tools for use by stakeholders to manage the disease. From a societal perspective, the research will assist decision makers in reducing HCV disease burden. The team is engaged with the Centers for Disease Control and Prevention (CDC), State and County health departments, and the World Health Organization (WHO), who are the potential stakeholders of the research. This project will also provide learning and research experience to students and fellows on the application of systems dynamic modeling to healthcare.This research will apply methodologies from epidemiology and operations research to provide decision support for the allocation of limited resources to effective intervention policies to contain the ongoing epidemic of HCV. The research team will address several important research questions related to hepatitis C management and control by 1) conducting surveys to estimate HCV prevalence in at-risk populations; 2) estimating the true HCV prevalence at the State and National level via a validated agent-based simulation model; 3) researching optimization-based approaches to dynamic allocation of adaptive intervention strategies. The research is expected to lead to practical decision support. The research will advance knowledge in mathematical and computational modeling of infectious diseases and guide the allocation of limited resources towards eliminating HCV as a global health threat.

慢性丙型肝炎病毒（HCV）感染是一个全球健康问题，比其他常见的感染状况（包括艾滋病毒/艾滋病，结核病和疟疾）导致死亡更多。 由于感染的潜伏期很长，症状很少，因此大多数感染者仍然没有意识到其健康状况。世界卫生组织（WHO）和美国国家医学院最近设定了一个雄心勃勃的目标，以便到2030年消除HCV；但是，存在一些挑战。 疾病的真正患病率是未知的，并且不存在有效的筛查政策，而治疗虽然有效，但非常昂贵。该项目具有以下三个总体目的：1）估计州和国家一级丙型肝炎的真正疾病负担； 2）确定有效的筛查和治疗策略来识别丙型肝炎感染； 3）设计实用的决策支持工具，用于利益相关者管理疾病。 从社会角度来看，该研究将帮助决策者减轻HCV疾病负担。该小组与疾病控制与预防中心（CDC），州和县卫生部门以及世界卫生组织（WHO）互动，这些组织是研究的潜在利益相关者。 该项目还将为学生和研究员提供有关系统动态建模在医疗保健中的应用。这项研究将应用流行病学和运营研究的方法，以为有限资源的有限资源分配给有效的干预政策提供决策支持，以包含HCV正在进行的流行病。研究小组将通过1）进行调查以估计高危人群中的HCV患病率来解决与乙型肝炎管理和控制有关的几个重要研究问题； 2）通过基于验证的代理模拟模型估算州和国家一级的真正HCV患病率； 3）研究基于优化的自适应干预策略动态分配的方法。 预计该研究将导致实际决策支持。该研究将提高有关传染病的数学和计算建模知识，并指导有限资源的分配以消除HCV作为全球健康威胁。

项目成果

Assessment of the Feasibility and Cost of Hepatitis C Elimination in Pakistan

• DOI: 10.1001/jamanetworkopen.2019.3613
• 发表时间: 2019-05-01
• 期刊: JAMA NETWORK OPEN
• 影响因子: 13.8
• 作者: Chhatwal, Jagpreet;Chen, Qiushi;Kanwal, Fasiha
• 通讯作者: Kanwal, Fasiha

Cost-Effectiveness and Value-of-Information Analysis Using Machine Learning–Based Metamodeling: A Case of Hepatitis C Treatment

使用基于机器学习的元建模进行成本效益和信息价值分析：丙型肝炎治疗案例

• DOI: 10.1177/0272989x221125418
• 发表时间: 2022
• 期刊: Medical Decision Making
• 影响因子: 3.6
• 作者: McCandlish, John Austin;Ayer, Turgay;Chhatwal, Jagpreet
• 通讯作者: Chhatwal, Jagpreet

PDG32 GAME-THEORETICAL ANALYSIS OF NETFLIX PAYMENT MODEL FOR HEPATITIS C TREATMENT

PDG32 丙型肝炎治疗 Netflix 支付模型的博弈论分析

• DOI: 10.1016/j.jval.2020.04.322
• 发表时间: 2020
• 期刊: Value in Health
• 影响因子: 4.5
• 作者: Ayer, T.;She, Z.;Zhuo, Y.;Chhatwal, J.
• 通讯作者: Chhatwal, J.

Changes in hepatitis C burden and treatment trends in Europe during the era of direct-acting antivirals: a modelling study

• DOI: 10.1136/bmjopen-2018-026726
• 发表时间: 2019-06-01
• 期刊: BMJ OPEN
• 影响因子: 2.9
• 作者: Chen, Qiushi;Ayer, Turgay;Chhatwal, Jagpreet
• 通讯作者: Chhatwal, Jagpreet

FEASIBILITY AND COST OF HEPATITIS C ELIMINATION IN CHINA

中国消除丙型肝炎的可行性和成本

• 发表时间: 2019
• 期刊: Hepatology
• 影响因子: 13.5
• 作者: Chhatwal, J;Zhuo, Y;Chen, Q;Zhan, T;Chen, W;Ayer, T;Nwankwo, C;Puenpatom, A
• 通讯作者: Puenpatom, A