SPEAKER: Sabina Alistar, Stanford Univ.

ABSTRACT:

Operations research and mathematical modeling can play a key role in informing high-cost, high-impact health policy decisions. This talk describes my research on resource allocation for infectious disease control. Resource allocation is especially difficult in this context because epidemics are nonlinear (preventing one infection now may prevent scores of future infections); interventions usually do not have additive effects, and the relationship between investment and outcomes is generally nonlinear; in addition, epidemics vary across settings in terms of transmission modes and key risk groups.

In theoretical work, I address the gap between epidemiological measures and the resource allocation decision. I present a new theoretical framework that quantifies the effects of investment in treatment and prevention interventions on a key epidemiological parameter, the reproductive rate of infection, which measures an outbreak’s potential for becoming an epidemic. The approach accounts for nonlinearities of intervention scale-up effects. I develop analytical results characterizing the optimal solution and present illustrative examples with data for Uganda and Russia. I further extend the framework to consider the optimal control in time of various epidemiological parameters.

In practical work, in collaboration with the United Nations AIDS Programme (UNAIDS) I have created a spreadsheet-based planning tool for use by planners around the world in evaluating investment portfolios for HIV control. The tool is designed to be easy to use, includes optimization capability, and accounts for non-additive and nonlinear effects of interventions.  I describe my ongoing work with UNAIDS decision makers to test and implement the model for regional and country-level HIV resource allocation.