RFA-AI-11-003 seeks to use implementation science to identify more efficient ways to increase the amount of health benefits from PEPFAR resources, with an emphasis on retention-in-care. We will expand on our prior model of HIV disease to create a model that will simulate the HIV epidemic in east Africa, taking into account person-to-person HIV transmission, in order to evaluate the benefit and value of retention-in-care interventions in east Africa. The model has been previously calibrated and validated using data from east Africa, and for the current proposal we will again use data from the International epidemiologic Databases to Evaluate AIDS (IeDEA) East Africa consortium, which has data on over 100,000 HIV-infected patients in East Africa. In addition, we will assess program-specific interventions using data from two PEPFAR-funded programs in Kenya and one in Uganda. Our investigators include infectious disease experts and epidemiologists with many years experience working with the aforementioned programs, including time spent working on the ground both as clinicians and as researchers.
We aim to (1) determine optimal packages of retention-in-care interventions for hypothetical programs across a range of patient, program, and health system characteristics, (2) determine how the value (additional benefit per additional cost) of retention-in-care packages compares to that of other interventions in resource-constrained settings, and (3) individualize optimal retention-in-care packages for 3 PEPFAR-funded programs in Kenya and Uganda, considering budgets as well as patient, program, and health system characteristics.
Loss to follow-up is a major problem facing HIV care programs in resource-limited settings and a barrier to ensuring best health outcomes for HIV-infected patients and their communities. We seek to use established computer simulation methods to assess the value of retention-in-care interventions and compare the value of these interventions to other ways in which resources may be spent. We will identify the packages of retention interventions that will maximize health outcomes for patients based on patient, program, and health system characteristics.
|Kessler, Jason; Braithwaite, R Scott (2013) Modeling the cost-effectiveness of HIV treatment: how to buy the most 'health' when resources are limited. Curr Opin HIV AIDS 8:544-9|