The costs of disease are immense, as is the amount of resources that societies put into combating disease through treatment, prevention, and the improvement of public health systems in general. Resources could be better allocated if the behavior and spread of diseases could be predicted. However, the spread of diseases such as influenza and HIV/AIDS depends on many complex factors — including the behavior of individuals, the public and private health environments that individuals are exposed to, and the evolution of disease-causing organisms in the face of pharmaceuticals — and only very detailed and costly simulations have been able to predict their epidemiology with any certainty. This dissertation attempts to “simulate the simulations” by using desktop models that capture the intent and the dynamics of more-detailed models. The dissertation consists of three papers: The first paper discusses the benefits of linking epidemiological modeling with international health resource allocation decisions; the second and third papers examine experimental models of influenza outbreak and antiretroviral policy in the context of India. Together, the papers present a method of simulating disease that can provide policymakers with useful information for assessing the costs and benefits of various interventions in the face of uncertainty.
This document was submitted as a dissertation in April 2008 in partial fulfillment of the requirements of the doctoral degree in public policy analysis at the Pardee RAND Graduate School. The faculty committee that supervised and approved the dissertation consisted of C. Richard Neu (Chair), Rob Boer, Theodore Karasik, and Steven Bankes (Carnegie Mellon University). Professor Maureen Cropper (University of Maryland) was the external reader. Financial support for this dissertation was provided by RAND's Arroyo Center and the Development Economics Research Group at the World Bank, Washington D.C.
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