Impact of ARV Chemoprophylaxis on Emergence and Spread of HIV Drug Resistance

抗逆转录病毒药物预防对艾滋病毒耐药性出现和传播的影响

• 批准号: 7545210
• 负责人: UME L ABBAS
• 金额: $ 24.37万
• 依托单位: CLEVELAND CLINIC LERNER COM-CWRU
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-25 至 2010-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7545210
• 关键词: Address; Anti-Retroviral Agents; Attention; Behavioral; Biological; CD4 Positive T Lymphocytes; Chemoprophylaxis; Clinical Trials; Complex; Computer Simulation; Development; Disease Progression; Drug resistance; Effectiveness; Epidemic; Epidemiologic Studies; Epidemiology; Equation; Evolution; Foundations; Generations; Goals; HIV; HIV vaccine; Health Benefit; Health Policy; Heterogeneity; Heterosexuals; Human; Incidence; Individual; Intervention; Knowledge; Life; Markov Chains; Methods; Minor; Modeling; Outcome; Pattern; Persons; Plasma; Population; Prevalence; Prophylactic treatment; Public Health; Research; Resources; Risk; Risk Behaviors; Safety; Simulate; Structural Models; Testing; Time; Uncertainty; Validity and Reliability; Variant; Viremia; Virus Diseases; Work; animal data; base; design; innovation; insight; interest; mathematical model; models and simulation; multi-scale modeling; mutant; novel; pandemic disease; prevent; transmission process; trend; virus pathogenesis

DESCRIPTION (provided by applicant): 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 proposal 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. PUBLIC HEALTH RELEVANCE: The proposed research is innovative in that we will use newly developed mathematical and computational models to analyze the patterns and determinants of spread of HIV drug resistance under different antiretroviral chemoprophylaxis strategies. Our work will help identify antiretroviral chemoprophylaxis strategies with maximal public health benefit and thereby guide public health policy.

描述（由申请人提供）：抗逆转录病毒预防预防对人免疫缺陷病毒（HIV）耐药性的发育和异性传播的潜在影响尚不清楚，尚未对其进行建模。该提案将使用新一代的数学和计算模型来研究抗逆转录病毒预防性对HIV耐药性的流行病学模式的影响，这些数学和计算模型代表了现实的生物学，人口统计学，流行病学和行为异质性，这些模型构成了HIV耐药性动力学的基础。这些创新的模型：i）纳入血浆病毒血症的变化，CD4细胞下降，HIV疾病进展，传染性，风险行为以及抗逆转录病毒性预防性的影响以及个体内部和之间的影响； ii）模拟化学预防使用的不同策略； iii）预测人群水平上的HIV耐药性结果。我们的长期目标是使用建模和仿真来设计公共卫生干预策略，以帮助控制全球艾滋病毒流行。中心假设是，针对传播和获取HIV感染风险最高的人的特定亚群可以最大程度地减少HIV耐药性的传播。提出的具体目的是：i）在抗逆转录病毒化学预防的不同情况下模拟HIV流行，并分析HIV耐药性的预测模式； ii）确定艾滋病毒耐药性预测模式的关键决定因素，并评估预测不确定性； iii）确定模型预测对建模框架和假设的敏感性。拟议的研究是新颖的，因为多种建模方法和建模量表将用于模拟不同抗逆转录病毒化学预防策略对资源限制环境中HIV耐药性的发病率和患病率的影响。我们的发现应有助于确定HIV耐药性传播的关键决定因素以及最有效的抗逆转录病毒预防策略，以遏制全球HIV流行和耐药性。 公共卫生相关性：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分析不同抗逆转录病毒化学预防策略下HIV耐药性传播的模式和决定因素。我们的工作将有助于确定具有最大公共卫生利益的抗逆转录病毒预防策略，从而指导公共卫生政策。