New Horizons in Modeling and Simulation for Social Epidemiology and Public Health

描述（由申请人提供）：世界卫生组织将健康的社会决定因素定义为“人们出生，成长，生活，工作和年龄的条件”。这些社会决定因素包括我们的邻里和工作环境（例如，食品环境）以及社会和经济政策（例如，税收政策），管理我们生活的地区。正是这些“上游”非医疗因素越来越被理解为健康不平等的根源。社会流行病学领域的重点是确定社会决定因素对人口健康的影响，而有关教育，住房和税收等政策的决定，以改善公共福利，是社会政策领域的核心。然而，在这两个领域中，由于缺乏对系统复杂性的考虑，使用传统模型确定影响是有限的。为了描绘健康的社会决定因素在整个社会的复杂系统中的真实影响，其特征是多个代理，非线性和反馈回路，需要新的建模和仿真工具。基于Agent的建模（ABM）和微观仿真模型（MSM）是两种这样的创新工具，它们可以对复杂系统进行建模和仿真，以更好地反映真实的世界。ABM和MSM对人口健康的社会决定因素的可能应用是巨大的，从建模棘手的问题，如肥胖流行病，到模拟制定新的税收政策对健康的影响。与包括社会科学在内的其他领域相比，在社会流行病学和公共卫生领域采用这些方法的情况很少。2006年，美国国立卫生研究院的行为和社会科学研究办公室（OBSSR）将系统科学方法作为其四个核心优先事项之一。这项NLM G13资助的目标是根据PI与John Wiley & Sons的合同，为一本名为《社会流行病学和公共卫生建模与模拟的新视野》的新书撰写手稿。这本书将提供一个国家的最先进的，关键的综合文献的建模和模拟方法，特别是：1）ABM;和2）男男性接触者，以更好地了解健康的社会决定因素。我们提出以下具体目标：1）为ABM和MSM的应用奠定概念和方法论基础，以“解开”健康的社会决定因素; 2）提供ABM和MSM在社会科学和社会流行病学/公共卫生实证研究中的应用的系统性综述; 3）强调未来使用ABM和MSM的研究方向，并讨论其政策含义。我们的团队由具有社会流行病学/公共卫生，社会科学，ABM和MSM互补专业知识的调查人员组成。总的来说，这本书将提供一个新的系统科学方法的丰富的综合解开社会决定因素对健康的复杂影响。因此，它将听从NIH的呼吁，在健康研究中采用系统方法，并推动运动，以拥抱公共卫生复杂系统的跨学科研究。从长远来看，这本书应该推动社会流行病学和公共卫生领域的发展，并通过指导决策者的决策来最佳地改善人口健康。

DESCRIPTION (provided by applicant): 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.