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

描述（由申请人提供）：注射吸毒者（IDU）中丙型肝炎（HCV）和人类免疫缺陷（HIV）病毒的负担仍然是一个重大的公共卫生挑战。不幸的是，既没有预防性HCV疫苗，也没有预防性疫苗或治愈艾滋病毒。目前，慢性HCV感染只能用聚乙二醇干扰素α和利巴韦林治疗，大多数患者不能获得持续的病毒应答。在HCV和HIV合并感染的情况下，HCV的预后可能更差，因为HIV已被证明加速HCV疾病进展并降低治疗反应。今天，预防HCV和HIV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，仍然有大量的人不知道他们感染了这两种病毒， 这两种情况，以及大量的个人没有或有限的获得任何治疗。基于“艾滋病毒治疗即预防”战略的成功，我们建议评估一个平行的“丙型肝炎病毒治疗即预防”战略。本研究的具体目的是：1.建立一个微观模拟数学模型，以评估增加HCV治疗覆盖率的影响，在HCV单一感染和HCV/HIV合并感染的IDU中，作为预防HCV和HIV传播的手段; 2.探索不同的建模风险结构的“谁从谁获得感染”，基于注射的风险行为，告知微观模拟模型的性质的传播动力学，并使用此结果来预测干预措施的影响。将通过预测未来的发病率、流行率、发病率和死亡率来衡量这一拟议干预措施的影响。我们的建模工作将考虑这种策略在基于不同HCV治疗覆盖率的各种情况下的潜在影响。本研究将基于已发表的pegIFN-RBV疗效和有效性数据。幸运的是，HCV的治疗目前正在经历重大的演变，这些新的抗HCV药物中有几种已经显示出有希望的结果。因此，所提出的数学模型将是灵活的，因此，它将能够适应正在进行的这些新的HCV药物的疗效和有效性试验的结果。相关性：没有时间等待“完美的方案”或预防HCV的疫苗。如果我们迅速采取行动，利用现有和更新的药物，许多生命将得到挽救。如果不这样做，将导致本可避免的医疗成本，并给已经在努力科普现有需求的医疗系统带来进一步的压力。这项拟议的研究有可能推进运筹学领域，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HCV单感染和HCV/HIV共感染的注射吸毒者。

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.