IMPACT OF ANTIRETROVIRAL PREVENTION ON EMERGENCE AND SPREAD OF HIV DRUG RESISTA

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得主要资金， 因此可以在其他CRISP条目中表示。列出的机构是 中心，不一定是研究者的机构。 抗逆转录病毒暴露前预防对发展的潜在影响 艾滋病毒（艾滋病毒）的传播和异性性传播 电阻是未知的，并且尚未建模。该项目将调查 抗逆转录病毒药物预防对HIV药物流行病学模式的影响 使用新一代的数学和计算模型， 代表了现实的生物学、人口学、流行病学和行为学 HIV耐药性的异质性。这些创新 模型：i）纳入血浆病毒血症、CD 4细胞下降、HIV疾病 疾病进展、传染性、危险行为和抗逆转录病毒治疗的效果 个体内和个体间的化学预防; ii）模拟不同的策略 和iii）预测艾滋病毒耐药性的结果， 人口水平。我们的长期目标是使用建模和仿真来设计 这将有助于控制全球艾滋病毒流行的公共卫生干预战略。 核心假设是，针对特定的亚群人， 传播和获得HIV感染的风险可以最大限度地减少HIV药物的传播 阻力提出的具体目标是：i）模拟艾滋病毒的流行， 抗逆转录病毒药物预防的不同方案实施和分析 艾滋病毒耐药性的预测模式; ii）确定艾滋病毒耐药性的关键决定因素， HIV耐药性的预测模式，并评估预测结果 不确定性;以及iii）确定模型预测对建模的敏感性 框架和假设。这项研究的新颖之处在于， 模拟方法和模拟尺度将用于模拟 不同的抗逆转录病毒药物预防策略对发病率和患病率的影响 在资源有限的环境中，艾滋病毒耐药性的问题。我们的发现应该有助于确定 艾滋病毒耐药性传播的关键决定因素， 抗逆转录病毒药物预防战略，以遏制全球艾滋病毒流行， 耐药性

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The potential impact of antiretroviral pre-exposure prophylaxis on the development and heterosexual transmission of human immunodeficiency virus (HIV) drug resistance is unknown and has not been modeled. This project will investigate the effect of antiretroviral chemoprophylaxis on the epidemiologic patterns of HIV drug resistance using a new generation of mathematical and computational models that represent realistic biological, demographic, epidemiologic and behavioral heterogeneities that underlie the dynamics of HIV drug resistance. These innovative models: i) incorporate variation in plasma viremia, CD4 cell decline, HIV disease progression, infectiousness, risk behavior, and effect of antiretroviral chemoprophylaxis both within and among individuals; ii) simulate different strategies of chemoprophylaxis use; and iii) predict HIV drug resistance outcomes at the population level. Our long term goal is to use modeling and simulation to design public health intervention strategies 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 minimize the spread of HIV drug resistance. The specific aims proposed are: i) to simulate an HIV epidemic under different scenarios of antiretroviral chemoprophylaxis implementation and analyze the predicted patterns of HIV drug resistance; ii) to identify the key determinants of the predicted patterns of HIV drug resistance and evaluate the prediction uncertainty; and iii) to determine the sensitivity of the model predictions to modeling framework and assumptions. The proposed research is novel in that multiple modeling approaches and modeling scales will be used to simulate the effect of different antiretroviral chemoprophylaxis strategies on the incidence and prevalence of HIV drug resistance in resource-limited settings. Our findings should help identify the key determinants for spread of HIV drug resistance and the most effective antiretroviral chemoprophylaxis strategies to curb both the global HIV epidemic and drug resistance.