Simulation Tool for HIV/STD Cost-Effectiveness Analysis

描述(由申请人提供)：本申请请求支持一项为期3年的研究计划，以开发一种基于计算机的艾滋病毒/性传播疾病传播模拟模型，该模型可应用于性风险降低干预数据集，以生成对这些干预措施的有效性和成本效益的更准确和更有信息的估计。因为需要资金支持艾滋病毒/性传播疾病预防干预措施，以确保实施最经济有效的干预措施，并确保艾滋病毒/性传播疾病预防资源得到最大限度的利用。为了满足这一需求，我们的研究小组和其他人启动了研究计划，利用艾滋病毒/性传播疾病传播的数学模型来评估性风险降低干预措施的成本效益，以估计这些干预措施避免的感染数量。然而，这些“决定论”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，而且不容易扩展到纳入影响艾滋病毒/性传播疾病传播的时变或人口分布因素。所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拟人群内和随时间随机变化；(2)明确地模拟传播风险活动的时间，从而允许干预参与者在干预评估期间感染STD时发生的“动态”感染；(3)同时模拟多种STD(包括HIV)的传播和STD之间的协同作用；以及(4)以成本-效果比分布和可信区间的形式生成成本-效果结果的更多信息特征，而不仅仅是确定性模型产生的成本-效果点估计。该模拟模型可应用于各种性行为风险降低干预数据集、研究设计和干预策略，以估算HIV/STD干预的成本效益。对于干预研究人员、项目评估者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有关人员来说，该模拟模型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.