The WHO defines the social determinants of health as "the conditions in which people are born, grow, live, work and age". These social determinants include our neighborhood and workplace environments (e.g., the food environment) and the social and economic policies (e.g., tax policies) that govern the regions in which we live. It is these "upstream" non-medical factors that are increasingly understood as the root causes of health inequalities. Identifying what impacts social determinants have on population health is the focus of the field of social epidemiology, whereas decisions concerning policies such as education, housing, and taxation to improve public welfare are central to the social policy field. Yet in both of these fields, identifying impacts using traditional models is limited by lack of consideration of the complexity of systems. In order to delineate the true effects of the social determinants of health within the complex systems of entire societies-characterized by multiple agents, non-linearities, and feedback loops-novel modeling and simulation tools are required. Agent- based modeling (ABM) and microsimulation models (MSM) are two such innovative tools that can model and simulate complex systems, to better mirror the real world. Possible applications of ABM and MSM to the social determinants of population health are vast, ranging from modeling intractable problems such as the obesity epidemic, to simulating the health impacts of enacting new tax policies. By contrast to other fields including the social sciences, adoption of these approaches in social epidemiology and public health is sparse. In 2006, the NIH's Office of Behavioral and Social Sciences Research (OBSSR) made systems science approaches one of its four core priorities. The goal of this NLM G13 grant is to write the manuscript for a new book entitled New Horizons in Modeling and Simulation for Social Epidemiology and Public Health, under contract by the PI with John Wiley &Sons. This book will provide a state-of-the-art, critical synthesis of the literature on modeling and simulation approaches, in particular: 1) ABM;and 2) MSM, to better understand the social determinants of health. We propose the following Specific Aims: 1) to lay a conceptual and methodological foundation for the application of ABM and MSM to "unpack" the social determinants of health;2) to provide a systematic review of ABM and MSM applications in empirical research in the social sciences and social epidemiology/public health;and 3) to highlight future directions for research using ABM and MSM, and discuss their policy implications. Our team consists of investigators with complementary expertise in social epidemiology/public health, social sciences, and ABM and MSM. Overall, this book will offer a rich synthesis of novel systems science approaches to disentangle the complex impacts of social determinants on health. It will thereby heed NIH's calls for systems approaches in health research, and advance the movement to embrace the interdisciplinary study of complex systems in public health. Over the long term, this book should propel the social epidemiology and public health fields forward, and by guiding policymakers'decisions optimally improve population health.
(PUBLIC HEALTH RELEVANCE) Through this grant, the PI will write the manuscript for a new book entitled New Horizons in Modeling and Simulation for Social Epidemiology and Public Health. This book will provide a rich synthesis of key modeling and simulation approaches to better understand the complex impacts of social determinants on population health. Over the long term, this work should advance the fields of social epidemiology and public health, and through guiding policymakers'future decisions optimally improve population health.