Alton Russell – MGH Institute for Technology Assessment, Harvard Medical School
Since HIV and Hepatitis C epidemics in the 1980’s, keeping the supply of donate blood free of disease has been a public health priority. Decision-analytic modeling can inform blood safety policy by elucidating trade-offs between costs, risks, and supply sufficiency. This talk will describe three projects that aim to inform blood safety policy. The first project is a cost-effectiveness analysis of the US policy of screening all blood donations for Zika virus. This analysis uses a novel microsimulation of individual transfusion recipients that captured the relationship between disease exposure risk and the number and type of blood components transfused. The second project is the first cost-effectiveness analysis of whole blood pathogen inactivation, a technology that reduces risk of adverse outcomes in patients receiving blood transfusions. The analysis is for Ghana and improves on prior blood safety assessments for sub-Saharan Africa by considering the likelihood and timing of clinical detection for chronic viral infections. In the third project, I develop an optimization-based framework for identifying the optimal portfolio of blood safety interventions across three modalities: deferring high-risk donors, testing for disease markers, and using risk-reducing modifications (e.g., pathogen reduction) which prevent disease transmission. This framework overcomes limitations of traditional cost-effectiveness analyses for blood safety. These three projects use decision-analytic modeling to inform the efficient use of limited resources for blood safety.