Falling Short of Expectations: Improving Policy Design in Global Health

Abstract

This dissertation is comprised of three studies that examine three global and national-level policies, and apply different quantitative analyses to improve the research base that informs these policies, with the aim of ultimately improving the designs of existing health policies. Chapter 2 examines the UNAIDS’ goal to eliminate AIDS by 2030. It combines survival analysis of a longitudinal dataset and a Markov model of progression through different stages of HIV care cascade, and find that the mathematical models that informed the UNAIDS’ policy overestimates the health benefits that could be realized in real life. Chapter 3 examines South Africa’s Integrated Chronic Disease Management model, using regression models I conclude that how different types of multimorbidity affects the care patients receive should be considered when designing care delivery in order to provide coherent and efficient care. Chapter 4 assesses the target set by the Global Vaccine Action Plan, which aims to improve health equity through providing equal access to vaccines. I developed a methodology to quantify the impact of different vaccine coverage scenarios with respect to household income that take into account the distribution of other risk factors. I conclude in this chapter that merely ensuring equal access to vaccines will not reduce health outcome gaps across income quintiles because of the differences in the distribution of risks and the treatment provided.