Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, 10032, USA.
Mailman School of Public Health, ICAP at Columbia University, 722 West 168th Street, New York, 10032, USA.
Curr HIV/AIDS Rep. 2024 Jun;21(3):140-151. doi: 10.1007/s11904-024-00695-z. Epub 2024 Mar 13.
HIV service delivery programs are some of the largest funded public health programs in the world. Timely, efficient evaluation of these programs can be enhanced with methodologies designed to estimate the effects of policy. We propose using the synthetic control method (SCM) as an implementation science tool to evaluate these HIV programs.
SCM, introduced in econometrics, shows increasing utility across fields. Key benefits of this methodology over traditional design-based approaches for evaluation stem from directly approximating pre-intervention trends by weighting of candidate non-intervention units. We demonstrate SCM to evaluate the effectiveness of a public health intervention targeting HIV health facilities with high numbers of recent infections on trends in pre-exposure prophylaxis (PrEP) enrollment. This test case demonstrates SCM's feasibility for effectiveness evaluations of site-level HIV interventions. HIV programs collecting longitudinal, routine service delivery data for many facilities, with only some receiving a time-specified intervention, are well-suited for evaluation using SCM.
综述目的：艾滋病毒服务提供计划是世界上规模最大的公共卫生计划之一。通过专门设计的评估方法，及时、有效地评估这些计划可以提高效率。我们提出使用合成控制法（SCM）作为实施科学工具来评估这些艾滋病毒计划。
最新发现：SCM 最初在计量经济学中提出，现在已在各个领域得到越来越多的应用。与传统的基于设计的评估方法相比，这种方法的主要优点在于通过对候选非干预单位进行加权，直接近似干预前的趋势。我们使用 SCM 来评估针对近期感染人数较多的艾滋病毒卫生机构的公共卫生干预措施的效果，该措施旨在提高预防暴露前预防（PrEP）的参与率。这个测试案例表明 SCM 可以有效地评估针对艾滋病毒的现场干预措施。对于收集了许多设施的纵向、常规服务提供数据，但只有一些设施在特定时间内接受干预的艾滋病毒项目来说，使用 SCM 进行评估非常合适。
