Synthetic Controls for Implementation Science: Opportunities for HIV Program Evaluation Using Routinely Collected Data

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.