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者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尚不清楚，也没有充分的模型。这项提议将使用新一代数学和计算模型来调查抗逆转录病毒治疗和化学预防对艾滋病毒异性传播的影响，这些模型代表了艾滋病毒异性传播背后现实的生物和行为异质性。这些创新的模型：i)将血浆病毒血症、CD4细胞下降、艾滋病毒疾病进展、传染性、危险行为和对抗逆转录病毒治疗的反应的变化纳入个人内部和个人之间；ii)模拟不同的抗逆转录病毒使用策略；iii)在人群水平预测艾滋病毒流行结果。我们的长期目标是使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。中心假设是，以传播和感染艾滋病毒感染风险最高的特定人群为目标，可以最大限度地发挥抗逆转录病毒药物对艾滋病毒流行的影响。建议的具体目标是：1)使用三种不同的建模方法--微分方程式、离散事件系统和指数随机图，建立和分析一套在资源有限的情况下类似但越来越准确的异性艾滋病毒流行模型；2)确定哪些艾滋病毒感染者应该接受抗逆转录病毒治疗，以最大限度地发挥抗逆转录病毒疗法对艾滋病毒异性传播的影响；以及3)比较对感染者的抗逆转录病毒治疗和对艾滋病毒易感者的抗逆转录病毒化学预防的效果。这项拟议的研究具有创新性，因为我们将使用新开发的数学和计算模型来模拟不同艾滋病毒预防战略在资源有限的情况下的有效性。我们的发现应该有助于确定最有效的抗逆转录病毒战略，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.