Computational modeling for HCV vaccine trial design and optimal vaccine-based combination interventions

HCV 疫苗试验设计和基于疫苗的最佳组合干预措施的计算模型

• 批准号: 10514625
• 负责人: Basmattee Boodram
• 金额: $ 70.81万
• 依托单位: LOYOLA UNIVERSITY CHICAGO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-11-01 至 2026-10-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10514625
• 关键词: Advisory Committees; Affect; Antiviral Agents; Antiviral Therapy; Area; Behavioral; COVID-19; COVID-19 vaccine; Caring; Chicago; Chronic; Chronic Hepatitis C; Cities; Clinical Trials; Clinical Trials Design; Communities; Complex; Computer Models; Country; Data; Diagnosis; Disease; Disparate; Drug usage; Epidemic; Epidemiologist; Future; Geographic Factor; Geography; Goals; Harm Reduction; Health; Hepatitis C; Hepatitis C Antiviral; Hepatitis C Incidence; Hepatitis C Therapy; Hepatitis C Transmission; Hepatitis C Vaccine; Hepatitis C virus; Illinois; Immunity; Immunologist; Incidence; Individual; Infection; Injecting drug user; Injections; Intervention; Kinetics; Licensing; Literature; Location; Modeling; Modification; Needle-Exchange Programs; Outcome; Patients; Persons; Pharmaceutical Preparations; Policy Maker; Population; Predisposition; Prevalence; Public Health; Research; Research Personnel; Risk; Risk Behaviors; SARS-CoV-2 transmission; San Francisco; Site; Social Network; Statistical Data Interpretation; United States; United States Dept. of Health and Human Services; Vaccine Clinical Trial; Vaccine Design; Vaccines; Viral; Viral Load result; Viral hepatitis; Work; World Health; attenuation; chronic infection; clinical trial recruitment; combination intervention strategy; design; epidemic virus; follow-up; global health; high risk population; in silico; injection drug use; interdisciplinary collaboration; mathematical model; medication for opioid use disorder; metropolitan; pathogen; placebo group; prevent; randomized, clinical trials; recruit; social; social norm; structural determinants; success; successful intervention; transmission process; trial design; uptake; vaccination outcome; vaccine development; vaccine efficacy; vaccine trial; viral RNA

PROJECT SUMMARY/ABSTRACT Despite remarkable progress with direct-acting antivirals (DAAs), hepatitis C virus (HCV) infection remains a serious global public health problem with over 1% of the world’s population and about 3 million in the United States (U.S.) infected. The U.S. Department of Health & Human Services recently renewed the Action Plan to Prevent, Care and Treat Viral Hepatitis to eliminate viral hepatitis infection as a public health threat and the WHO introduced global targets for the care and management of HCV. While the highest uptake of HCV treatment occurred in 2017 and 1.5 million people were cured, 1.6 million new infections occurred. Due to many treatment barriers, only an estimated 21% of infected patients are diagnosed and only 2% of total infected patients are being treated for the disease annually. DAAs alone are unlikely to achieve HCV elimination; as such, the development of a vaccine to prevent HCV infection is an important focus of ongoing research. Vaccine clinical trials for HCV infection will need to recruit from high-risk populations, such as persons who inject drugs (PWID), who contribute an estimated 60% of all new HCV infections in the U.S. and have an increasing incidence of HCV, especially among young PWID. Additionally, limited access to DAA treatment, syringe service programs (SSP), and continued injection drug use poses challenges among PWID even as treatment with medication for opioid use disorder (MOUD) is expanding. Factors contributing to transmission and successful intervention (DAAs, MOUD, SSP) among PWID are dynamic and complex and occur at the individual (e.g., pathogen-host interplay, risk behaviors), social (e.g., injection network, social norms), structural (e.g., access to SSP and MOUD), and geographic (e.g., interaction locations) levels. As such, performing HCV vaccine randomized clinical trials (RCT) in the PWID population presents major challenges. We propose to develop an integrated comprehensive computational modeling approach to examine these challenges systematically and assess the impact of specific RCT modifications on clinical trial success. To explore vaccine trial design and outcomes, our interdisciplinary team will: (1) design and evaluate clinical trials in low incidence PWID sites, using metropolitan Chicago as the model, which reduces the chance of someone becoming exposed before being fully protected; (2) design and evaluate clinical trials in high incidence PWID sites, using San Francisco as the model, which increases the chance of someone becoming exposed before being fully protected; and (3) discover effective HCV vaccine-based intervention strategies to achieve WHO elimination goals in the context of a licensed vaccine. The literature supports that non-sterilizing vaccines are expected to be the focus of future trials, reminiscent of recent COVID-19 vaccines, therefore we will simulate their effect on transmission to reach elimination. We will account for SSP and MOUD and their effect on outcomes in two cities with disparate HCV epidemic profile among PWID—Chicago and San Francisco.

项目总结/摘要 尽管直接作用抗病毒药物（DAA）取得了显着进展，但丙型肝炎病毒（HCV）感染仍然是一个严重的问题。 严重的全球公共卫生问题，占世界人口的1%以上，美国约有300万人 州（美国）感染了美国卫生与公众服务部最近更新了行动计划， 预防、护理和治疗病毒性肝炎，以消除病毒性肝炎感染对公共卫生的威胁，世卫组织 为HCV的护理和管理制定了全球目标。虽然HCV治疗的最高吸收率 2017年发生了150万人被治愈，160万人新感染。由于许多治疗 由于存在障碍，估计只有21%的感染患者被诊断出来，只有2%的感染患者被诊断出来， 每年都要接受治疗单独使用DAA不太可能实现HCV消除;因此， 预防HCV感染的疫苗的开发是正在进行的研究的重要焦点。 HCV感染的疫苗临床试验将需要从高危人群中招募， 注射毒品者（PWID），估计占美国所有新HCV感染的60%， 丙型肝炎的发病率增加，特别是在年轻的PWID中。此外，DAA治疗的机会有限， 注射器服务计划（SSP）和继续注射毒品的使用构成了挑战，即使在PWID 阿片类药物使用障碍（MOUD）的药物治疗正在扩大。导致传播的因素， PWID中的成功干预（DAA、MOUD、SSP）是动态和复杂的，发生在个体身上 (e.g.,病原体-宿主相互作用，危险行为），社会（例如，注入网络，社会规范），结构性（例如， 对SSP和MOUD的访问），以及地理（例如，交互位置）水平。因此，执行HCV疫苗 PWID人群的随机临床试验（RCT）提出了重大挑战。我们建议发展一个 综合全面的计算建模方法，系统地研究这些挑战， 评估特定RCT修改对临床试验成功的影响。 为了探索疫苗试验设计和结果，我们的跨学科团队将：（1）设计和评估 在低发病率PWID站点进行的临床试验，使用大都市芝加哥作为模型， （2）设计和评估高风险的临床试验; 发病率PWID网站，使用旧金山弗朗西斯科作为模型，这增加了某人成为 发现有效的基于HCV疫苗的干预策略， 在获得许可的疫苗的情况下实现世卫组织的消除目标。文献支持非灭菌 疫苗预计将成为未来试验的重点，让人想起最近的COVID-19疫苗，因此我们 将模拟它们对传播的影响，以达到消除。我们将考虑SSP和MOUD及其效果 在两个城市的结果与不同的丙型肝炎病毒流行概况之间的PWID-芝加哥和旧金山弗朗西斯科。