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

社会流行病学和公共卫生建模和模拟的新视野

基本信息

批准号：
8919447
负责人：
Daniel Kim
金额：
$ 4.8万
依托单位：
NORTHEASTERN UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-01 至 2017-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8919447
关键词：
Adoption Age Alcohol consumption Behavior Books Cancer Intervention and Surveillance Modeling Network Communicable Diseases Complex Contracts Developed Countries Drug usage Economic Policy Economics Education Empirical Research Environment Epidemic Epidemiologist Epidemiology Feedback Foundations Funding Future Goals Grant Health Healthcare Healthcare Systems Housing Income Interdisciplinary Study International Life Life Expectancy Literature Manuscripts Marmota Methodology Methods Modeling Movement National Institute of General Medical Sciences Nature Neighborhoods Obesity Plant Roots Policies Public Health Research Research Personnel Science Social Environment Social Impacts Social Policies Social Sciences Social Welfare Societies Son Surveys System Taxation Taxes United States United States National Institutes of Health Work Workplace World Health Organization Writing base behavioral/social science built environment food environment health inequalities improved infectious disease model innovation models and simulation novel policy implication population health public health relevance research study social social health determinants social model social science research systematic review tool

项目摘要

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.

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、工作和衰老的条件”。这些社会决定因素包括我们的社区和工作场所环境（例如食品环境）以及管理我们居住地区的社会和经济政策（例如税收政策）。正是这些“上游”非医疗因素越来越多地被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，而有关教育、住房和税收等改善公共福利的政策决策则是社会政策领域的核心。然而，在这两个领域，使用传统模型识别影响因缺乏对系统复杂性的考虑而受到限制。为了描绘整个社会复杂系统（以多主体、非线性和反馈循环为特征）中健康问题社会决定因素的真实影响，需要新颖的建模和模拟工具。基于代理的建模（ABM）和微观仿真模型（MSM）是两种这样的创新工具，可以对复杂系统进行建模和仿真，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潜在应用非常广泛，从对肥胖流行等棘手问题进行建模，到模拟制定新税收政策对健康的影响。与社会科学等其他领域相比，这些方法在社会流行病学和公共卫生领域的应用很少。 2006 年，NIH 行为与社会科学研究办公室 (OBSSR) 将系统科学方法列为其四个核心优先事项之一。 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。本书将提供有关建模和仿真方法的最先进的、批判性的文献综合，特别是： 1) ABM； 2) MSM，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）为应用ABM和MSM“解开”健康的社会决定因素奠定概念和方法基础； 2) 对 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进行系统回顾； 3) 强调使用 ABM 和 MSM 的未来研究方向，并讨论其政策影响。我们的团队由在社会流行病学/公共卫生、社会科学、ABM 和 MSM 方面具有互补专业知识的研究人员组成。总体而言，本书将提供新颖的系统科学方法的丰富综合，以阐明社会决定因素对健康的复杂影响。因此，它将响应美国国立卫生研究院 (NIH) 对健康研究系统方法的呼吁，并推动公共卫生复杂系统跨学科研究的运动。从长远来看，本书应推动社会流行病学和公共卫生领域向前发展，并通过指导政策制定者的决策，以最佳方式改善人口健康。