Impact of Antiretrovirals on the Spread of HIV

描述（由申请人提供）：艾滋病毒感染者的抗逆转录病毒治疗和艾滋病毒易感个体的抗逆转录病毒化学预防对人类免疫缺陷病毒（艾滋病毒）全球传播的潜在影响是未知的，并且尚未充分建模。该提案将利用新一代数学和计算模型来研究抗逆转录病毒治疗和化学预防对异性恋艾滋病毒传播的影响，这些模型代表了异性恋艾滋病毒传播背后的现实生物学和行为异质性。这些创新模型：i)纳入个体内部和个体之间血浆病毒血症、CD4细胞下降、艾滋病毒疾病进展、传染性、风险行为和对抗逆转录病毒治疗的反应的变异；Ii)模拟不同的抗逆转录病毒使用策略；㈢在人口一级预测艾滋病毒流行的结果。我们的长期目标是利用建模和模拟来设计有助于控制全球艾滋病毒流行的公共卫生干预措施。核心假设是，针对传播和感染艾滋病毒风险最高的特定亚群，可以最大限度地发挥抗逆转录病毒药物对艾滋病毒流行病的影响。提出的具体目标是：1)利用三种不同的建模方法——微分方程、离散事件系统和指数随机图，开发和分析一套类似但越来越准确的异性恋艾滋病毒流行模型；2)确定哪些艾滋病毒感染者应该接受抗逆转录病毒治疗，以最大限度地提高抗逆转录病毒治疗对艾滋病毒异性传播的影响；3)比较hiv易感人群抗逆转录病毒化学预防与感染者抗逆转录病毒治疗的有效性。拟议的研究是创新的，因为我们将使用新开发的数学和计算模型来模拟在资源有限的情况下不同的艾滋病毒预防策略的有效性。我们的发现应该有助于确定最有效的抗逆转录病毒策略，以遏制艾滋病毒的全球传播。

DESCRIPTION (provided by applicant): The potential impact of antiretroviral therapy of HIV-infected individuals and antiretroviral chemoprophylaxis of HIV susceptible individuals on the global spread of human immunodeficiency virus (HIV) is unknown and has not been adequately modeled. This proposal will investigate the effects of antiretroviral therapy and chemoprophylaxis on heterosexual spread of HIV using a new generation of mathematical and computational models that represent realistic biological and behavioral heterogeneities that underlie heterosexual spread of HIV. These innovative models: i) incorporate variation in plasma viremia, CD4 cell decline, HIV disease progression, infectiousness, risk behavior and response to antiretroviral therapy, both within and among individuals; ii) simulate different strategies of antiretroviral use; and iii) predict HIV epidemic outcomes at the population level. Our long-term goal is to use modeling and simulation to design public health interventions that will help control the global HIV epidemic. The central hypothesis is that targeting specific subpopulations of persons at highest risk for transmitting and acquiring HIV infection can maximize the impact of antiretrovirals on the HIV epidemic. The specific aims proposed are: 1) to develop and analyze a set of analogous yet increasingly accurate models of the heterosexual HIV epidemic in resource-limited settings, using three different modeling methods - differential equations, discrete event systems and exponential random graphs; 2) to identify which HIV-infected persons should receive antiretroviral therapy to maximize the effect of antiretroviral therapy on heterosexual transmission of HIV; and 3) to compare the effectiveness of antiretroviral therapy of infected individuals with antiretroviral chemoprophylaxis of HIV-susceptible persons. The proposed research is innovative in that we will use newly developed mathematical and computational models to simulate the effectiveness of different HIV prevention strategies in resource-limited settings. Our findings should help identify maximally effective antiretroviral strategies to curb the global spread of HIV.