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

描述(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居和工作场所环境(例如，食物环境)以及管理我们所在地区的社会和经济政策(例如，税收政策)。正是这些“上游”非医疗因素被越来越多地理解为健康不平等的根本原因。确定社会决定因素对人口健康的影响是社会流行病学领域的重点，而关于改善公共福利的教育、住房和税收等政策的决策则是社会政策领域的核心。然而，在这两个领域，由于缺乏对系统复杂性的考虑，使用传统模型识别影响受到限制。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--以多个代理人、非线性和反馈回路为特征--需要新的建模和模拟工具。基于代理的建模(ABM)和微仿真模型(MSM)是两种能够对复杂系统进行建模和仿真的创新工具，以更好地反映现实世界。ABM和MSM在人口健康的社会决定因素方面的可能应用是巨大的，从对肥胖流行病等棘手问题的建模，到模拟制定新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，NIH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。这笔NLMG13赠款的目标是为一本名为《社会流行病学和公共卫生的建模和模拟的新视野》的新书撰写手稿，这本书是由PI与John Wiley&Sons签订的合同。这本书将提供最先进的，批判性的关于建模和模拟方法的文献的综合，特别是：1)ABM；和2)MSM，以更好地理解健康的社会决定因素。我们提出的具体目标如下：1)为应用ABM和MSM“解开”健康的社会决定因素奠定一个概念和方法基础；2)系统地回顾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；以及3)突出ABM和MSM未来的研究方向，并讨论它们的政策含义。我们的团队由在社会流行病学/公共卫生、社会科学以及ABM和MSM方面具有互补专业知识的调查人员组成。总体而言，这本书将提供丰富的新的系统科学方法的综合，以理清社会决定因素对健康的复杂影响。因此，它将响应NIH在卫生研究中采用系统方法的呼吁，并推动公共卫生中复杂系统的跨学科研究。从长远来看，这本书应该会推动社会流行病学和公共卫生领域的发展，并通过指导政策制定者的决策以最佳方式改善人口健康。

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.