Modeling different strategies to reduce the public health impact of the HCV/HIV e

描述(申请人提供)：丙型肝炎病毒(丙型肝炎病毒)和人类免疫缺陷病毒(HIV)在注射吸毒者(IDU)中的负担仍然是一个主要的公共卫生挑战。不幸的是，既没有预防性的丙型肝炎疫苗，也没有预防性的疫苗或治愈艾滋病毒的方法。目前，慢性丙型肝炎病毒感染只能用聚乙二醇α干扰素和利巴韦林治疗，大多数患者无法实现持续的病毒应答。在丙型肝炎病毒和艾滋病毒混合感染的情况下，丙型肝炎病毒的预后可能会更差，因为艾滋病毒已被证明加速了丙型肝炎病毒的病情发展，降低了治疗反应。今天，预防丙型肝炎和艾滋病毒仍然至关重要，特别是在注射吸毒者中，因为终末期肝病已成为合并感染者死亡的主要原因。然而，仍然有大量的人没有意识到他们感染了或 这两种情况，以及大量个人无法或有限地获得任何治疗。基于“艾滋病毒治疗即预防”战略的成功，我们建议对平行的“丙型肝炎病毒治疗即预防”战略进行评估。这项研究的具体目的是：1.建立一个微观模拟数学模型，以评估在单一丙型肝炎病毒和丙型肝炎病毒/艾滋病病毒混合感染的注射吸毒者中，增加丙型肝炎病毒治疗覆盖率作为预防丙型肝炎病毒和艾滋病毒传播的手段的影响；2.基于注射危险行为，探索“谁从谁那里获得感染”的不同建模风险结构，以告知微观模拟模型关于传播动力学的性质，并利用这一结果预测干预措施的影响。这一拟议干预措施的影响将通过预测未来的发病率、流行率、发病率和死亡率来衡量。我们的建模工作将考虑这一战略在基于不同水平的丙型肝炎治疗覆盖率的不同情景下的潜在影响。这项研究将基于已发表的PEG干扰素-RBV的疗效和有效性数据。幸运的是，丙型肝炎病毒的治疗目前正在经历重大的演变，其中几种新的抗丙型肝炎病毒药物已经显示出令人振奋的结果。因此，建议的数学模型将是灵活的，因此，它将能够适应这些新的丙型肝炎病毒药物正在进行的疗效和有效性试验的新结果。相关性：没有时间等待“完美的方案”或预防丙型肝炎病毒的疫苗。如果我们迅速采取行动，利用现有和更新的药物，许多人的生命将得到拯救。如果做不到这一点，将导致本可避免的医疗成本，并给本已在努力应对现有需求的医疗体系带来进一步压力。这项拟议的研究具有推动运筹学领域发展的潜力，因为我们将开发一个疾病进展和传播的微观模拟模型，其中包括单一感染的丙型肝炎病毒和丙型肝炎病毒/艾滋病病毒混合感染的注射用药单位。

DESCRIPTION (provided by applicant): The burden of the hepatitis C (HCV) and the human immunodeficiency (HIV) viruses among individuals who inject drugs (IDU) remains a major public health challenge. Unfortunately, there is neither a preventive HCV vaccine, nor a preventive vaccine or a cure for HIV. Currently, chronic HCV infection can only be treated with peginterferon alfa and ribavirin and sustained viral response is not achieved by the majority of patients. In a setting of HCV and HIV co-infection, the prognosis of HCV can be even worse, since HIV has been shown to accelerate HCV disease progression and decrease treatment response. Today, prevention of HCV and HIV remains vital, especially among IDU, since end-stage liver disease has become the leading cause of death among co-infected individuals. However, there is still a large number of individuals unaware that they are infected with either or both conditions, and a large number of individuals with no or limited access to any of the treatments. Based on the success of the "HIV Treatment as Prevention" strategy, we propose to evaluate a parallel "HCV Treatment as Prevention" strategy. The specific aims of this study are: 1. To develop a micro-simulation mathematical model to assess the impact of increasing coverage of HCV treatment, among HCV mono- and HCV/HIV co-infected IDU, as means of prevention of both HCV and HIV transmission; 2. To explore different modeling risk structures of "Who Acquire Infection from Whom", based on injecting risk behaviors, to inform the micro-simulation model regarding the nature of the transmission dynamics and use this result to predict the impact of interventions. The impact of this proposed intervention will be measured by predicting future incidence, prevalence, morbidity and mortality rates. Our modeling efforts will consider the potential impact of this strategy under various scenarios based on differing levels of HCV treatment coverage. This study will be based on published efficacy and effectiveness data on pegIFN-RBV. Fortunately, the treatment for HCV is currently undergoing significant evolution, and several of these new anti-HCV drugs have shown promising results. Thus, the proposed mathematical model will be flexible, and therefore, it will be able to accommodate emerging results from ongoing efficacy and effectiveness trials of these new HCV drugs. RELEVANCE: There is no time to wait for the "perfect regimen" or a vaccine that will prevent HCV. Many lives will be saved if we act expeditiously taking advantage of the current and newer drugs. Failure to do so will lead to avoidable healthcare costs and further stress to healthcare systems already struggling to cope with the existing demand. This proposed study has the potential to advance the operations research field, since we will be developing a micro-simulation model of disease progression and transmission which includes both HCV mono-infected and HCV/HIV co-infected IDU.