Statistical Methods for Combination HIV Prevention Approaches

说明(由申请人提供)：本申请是对《筹资机会公告》RFA-MH-14-180《艾滋病毒综合预防方法(R01)的方法学和形成工作》的回应，旨在为设计、分析和实施综合艾滋病毒预防方法中的挑战性问题开发统计方法。在应用中，我们确定了研究人员、政策制定者和实践者在艾滋病毒联合预防方面面临的四个迫在眉睫的挑战：1)寻找强大且易于实施的试验设计(S)，以评估联合预防干预措施的有效性；2)评估联合预防方法对公共健康的影响；3)利用现有的政府监测系统来监测资源使用、改进项目实施和衡量联合预防干预措施的影响；以及4)评估复杂流行病模型的预测，尤其是因为它们可能被用于联合干预研究的规划。为了应对这些挑战，我们的目标是开发以下统计方法：1)因子设计，对经过审查的事件发生时间结果建立灵活的通用回归模型；2)时变归因风险函数，以评估联合预防干预覆盖范围对公众健康的影响；3)使用监测数据来告知社区联合预防的状况；以及4)评估模型预测，为正在进行的艾滋病毒联合预防临床试验提供信息。在拟议的工作完成后，拟开发的方法应提供一套有用的统计工具，以评估、比较、通报和预测艾滋病毒联合预防办法。

DESCRIPTION (provided by applicant): This application is in response to the Funding Opportunity Announcement (FOA) RFA-MH-14-180, entitled ''Methodologies and Formative Work for Combination HIV Prevention Approaches (R01),'' aiming to develop statistical methods for challenging issues in design, analysis and implementation of combination HIV prevention approaches. In the application, we identify four imminent challenges faced by researchers, policy makers and practitioners on HIV combination prevention: 1) searching powerful and easy-to-implement trial design(s) to assess the effectiveness of combined prevention interventions; 2) assessing the public health impact of a combination prevention approach; 3) utilizing established government surveillance systems to monitor resource use, improve program implementation and measure impact of combination prevention interventions; and 4) evaluating the predictions of complex epidemic models, particularly as they may be used in planning of combination intervention studies. To address these challenges, we aim to develop statistical methods for: 1) factorial design with a flexible general regression model for censored time-to-event outcomes,; 2) time-varying attributable risk function to assess the public health impact of combination prevention intervention coverage; 3) the use of surveillance data to inform status of combination prevention at community level; and 4) evaluating model prediction to inform ongoing HIV combination prevention clinical trials. Upon completion of the proposed work, the methods to be developed shall provide a useful set of statistical tools to assess, compare, inform and predict HIV combination prevention approaches.