Simulation Tool for HIV/STD Cost-Effectiveness Analysis

描述（由申请人提供）：本申请要求支持一个为期3年的研究项目，以开发一个基于计算机的艾滋病毒/性病传播模拟模型，该模型可应用于性风险降低干预数据集，以对这些干预措施的有效性和成本效益产生更准确和信息丰富的估计。因为需要资金来支持艾滋病毒/性病预防干预措施，以确保实施最具经济效益的干预措施，并最大限度地利用艾滋病毒/性病预防资源。为了满足这一需求，我们的研究小组和其他人已经启动了研究项目，利用艾滋病毒/性病传播的数学模型来评估降低性风险干预措施的成本效益，以估计这些干预措施所避免的感染数量。然而，这些“确定性”模型受到许多限制。值得注意的是，它们没有考虑到性伙伴关系和这些伙伴关系中的性行为的相对时间，也不容易扩大，以纳入影响艾滋病毒/性病传播的时变因素或人口分布因素。本文提出的模拟模型对这些模型进行了改进：(1)允许关键参数和结果在模型总体内和随时间随机变化；(2)明确建模传播风险活动的时间，从而允许“动态”感染，即当干预参与者获得性病，然后在干预评估期间将感染传播给一个或多个伴侣；(3)同时模拟多种性传播疾病（包括HIV）的传播和性传播疾病之间的协同作用；(4)以成本效益比分布和置信区间的形式产生更多信息的成本效益结果特征，而不仅仅是由确定性模型产生的成本效益点估计。该模拟模型可以应用于各种各样的性风险降低干预数据集、研究设计和干预策略，以估计HIV/STD干预的成本效益。对于干预研究人员、项目评估人员和其他需要灵活而标准化的模型来评估HIV/STD预防干预的成本效益的人员来说，这将是一个有价值的工具。

DESCRIPTION (provided by applicant): This application requests support for a 3-year program of research to develop a computer-based simulation model of HIV/STD transmission that can be applied to sexual risk reduction intervention data sets to generate more accurate and informative estimates of the effectiveness and cost-effectiveness of these interventions. Because funds to support HIV/STD prevention interventions is needed to ensure that the most economically-efficient interventions are implemented and that HIV/STD prevention resources are used to maximal benefit. To address this need, our research group and others have initiated research programs to assess the cost-effectiveness of sexual risk reduction interventions using mathematical models of HIV/STD transmission to estimate the number of infections averted by these interventions. These 'deterministic' models are subject to a number of limitations, however. Notably, they do not take into account the relative time of sexual partnerships and sexual acts within those partnerships, and are not easily extended to incorporate time-varying or population-distributed factors that influence HIV/STD transmission. The proposed simulation model improves upon these models by: (1) permitting key parameters and outcomes to vary randomly, both within the modeled population and over time; (2) explicitly modeling the timing of transmission risk activities, thereby allowing for "dynamic" infections that occur when an intervention participant acquires an STD, then transmits infection to one or more partners during the intervention assessment period; (3) simultaneously modeling transmission of multiple STDs (including HIV) and synergistic interactions between STDs; and (4) generating much more informative characterizations of cost effectiveness outcomes in the form of cost-effectiveness ratio distributions and confidence intervals, rather than just the cost-effectiveness point estimates that are produced by deterministic models. The simulation model--which can be applied to a wide variety of sexual risk reduction intervention data sets, study designs, and intervention strategies to estimate HIV/STD intervention cost-effectiveness--will be a valuable tool for intervention researchers, program evaluators, and other interested persons who require a flexible yet standardized model for assessing the cost-effectiveness of HIV/STD prevention interventions.