Advisors: Philippe J. Giabbanelli.Committee members: Nicholas Karonis; Jose J. Padilla; Michael Papka.Includes illustrations and maps.Includes bibliographical references.Policy formulation and implementation is a multi-dimensional process, which requires a common platform to build communication between all sides involved. The growing availability of data along with the development of information and communication technology solutions (ICTs) supports this process by providing virtual platforms to design and evaluate policies. This thesis seeks to develop systems for policy-making with an emphasis on exploring and identifying the interacting causes that shape health. Our computational methods are primarily applied to the cause of obesity. In particular, we identify the relationships between fast-food outlets and schools at a national level, whereas it was previously done at a city-level. This thesis goes beyond the development of virtual platforms, by also contributing to newer approaches to analyze their output. Specifically, we develop interactive visualizations to help decision-makers in finding key patterns from large simulations of complex systems. Overall, this work has a few limitations. Despite the wealth and scale of data used in our study, it neither captures every single aspect that drives population health, nor does it track them with high temporal and spatial accuracy. Future work should explore the application of our model as a test platform for possible interventions, for instance through usability studies with policy-makers and an extended cost-benefit analysis of simulation results.M.S. (Master of Science
