Virtual Population Obesity Prevention (VPOP) Labs: Computational, Multi-Scale Models for Obesity Solutions

虚拟人口肥胖预防 (VPOP) 实验室：肥胖解决方案的计算、多尺度模型

• 批准号: 9982009
• 负责人: Bruce Y Lee
• 金额: $ 53.78万
• 依托单位: GRADUATE SCHOOL OF PUBLIC HEALTH AND HEALTH POLICY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9982009
• 关键词: Address; Administrator; Adult; Affect; Anthropology; Area; Baltimore; Behavior; Behavioral; Behavioral Model; Biological; Biological Models; Body Weight Changes; Cities; Clinical; Communities; Complex; Computer Simulation; Computer software; Data; Data Collection; Data Set; Decision Making; Development; Eating Behavior; Economic Policy; Economics; Environment; Epidemiology; Equation; Event; Food; Funding Opportunities; Future; Genetic; Geographic Locations; Glass; Goals; Health; Healthcare; High Performance Computing; Individual; Intervention; Kinesiology; Leadership; Location; Measures; Methodology; Methods; Modeling; National Institute of Diabetes and Digestive and Kidney Diseases; New York City; Obesity; Obesity Epidemic; Outcome; Pathway interactions; Physical activity; Physiological; Physiology; Policies; Policy Maker; Population; Process; Sampling; Science; Social Network; Social Sciences; Sociology; Software Tools; Supercomputing; System; Testing; Third-Party Payer; Translating; Translations; United States; Universities; University resources; Work; base; built environment; design; discrete time; economic outcome; experience; experimental study; field study; innovation; insight; markov model; metropolitan; model development; models and simulation; multi-scale modeling; multidisciplinary; next generation; novel; nutrition; obesity in children; obesity prevention; programs; public health relevance; simulation; social group; tool; virtual; working group

 DESCRIPTION (provided by applicant): The obesity epidemic is a continuing and growing major global multi-scale problem. Designing appropriate policies and interventions has been challenging since obesity is a complex problem, crossing the following six scales: genetic, physiological, individual, group/social network, physical (built) environment, and societal. The overall goal of this proposed project is to develop the Virtual Populations for Obesity Prevention (VPOP), a software platform that can generate an agent-based model encompassing the six obesity- relevant scales of any metropolitan area that can help decision makers to design, evaluate, and test proposed (or existing) obesity interventions and policies. VPOP will bring multiple innovations by (1) being the first model to bring together and integrate the six different scales that affect obesity; (2) including novel representations of numerous pathways and relationships; (3) leading to new insights and targets for obesity-control policies and interventions; (4) being grounded in an unprecedented breadth and depth of real- world multi-scale obesity-related data; (5) heavily involving decision makers in multi-scale model development to maximize policy-relevancy and translation of VPOP results into useful action; (6) developing new ways of representing and visualizing multi-scale results; and (7) transforming obesity-related data collection and decision making. Our multi-disciplinary team is led by Global Obesity Prevention Center (GOPC), which focuses on developing and implementing multi-scale systems science approaches, methods, and tools to address obesity, and brings together experts from the Pittsburgh Supercomputing Center (PSC)/ Carnegie Mellon University (CMU), Cornell, and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). The proposed VPOP and our participation in Interagency Modeling and Analysis Group (IMAG), and Multi-scale Modeling Consortium (MSM) activities would substantially leverage our existing GOPC and PSC/CMU resources and efforts. This includes extensive field studies to provide a large and broad data set to help populate, calibrate, and validate the VPOP and forming a Stakeholder Working Group to guide VPOP development, testing, and implementation. Specific Aim 1 will develop VPOP, a platform that can generate a geospatially explicit computational model representing the six obesity-relevant scales for any metropolitan area. Specific Aim 2 will entail utilizing VPOP to generate multi-scale simulation models of two sample metropolitan areas (the Baltimore Metropolitan Statistical Area and New York City) to use to identify the key drivers of obesity in children and adults across the six different scales and determine which factors may be maximally sensitive to specific programs and policies. For Specific Aim 3, we will translate the VPOP- generated models to decision-making by working with key stakeholders, such as city policy makers, health and planning department leadership, healthcare administrators, clinicians, and third-party payers to test and optimize a specific set of obesity-control policies and interventions.

 描述（由申请人提供）：肥胖流行是一个持续且日益严重的全球性多尺度问题，因为肥胖是一个复杂的问题，跨越以下六个尺度：遗传、生理、个人、群体。 /社交网络、物理（建筑）环境和社会 该拟议项目的总体目标是开发肥胖预防虚拟人群（VPOP），这是一个软件平台，可以生成包含六种肥胖相关的基于代理的模型。任意的尺度可以帮助决策者设计、评估和测试拟议（或现有）肥胖干预措施和政策的大都市区将通过以下方式带来多项创新：(1) 成为第一个将六种不同的模式整合在一起的模式。 影响肥胖的量表；(2) 包括多种途径和关系的新颖表述；(3) 为肥胖控制政策和干预措施提供新的见解和目标；(4) 以前所未有的广度和深度为基础- 规模肥胖相关数据；（5）决策者参与多尺度模型开发，以最大限度地提高政策相关性并将 VPOP 结果转化为有用的行动；（6）开发表示和可视化多尺度结果的新方法； 7）转变肥胖相关数据我们的多学科团队由全球肥胖预防中心 (GOPC) 领导，专注于开发和实施解决肥胖问题的多尺度系统科学方法、方法和工具，并汇集了来自匹兹堡超级计算的专家。中心 (PSC)/卡内基梅隆大学 (CMU)、康奈尔大学和国家糖尿病、消化和肾脏疾病研究所 (NIDDK) 拟议的 VPOP 以及我们对跨机构建模和分析小组的参与。 (IMAG) 和多尺度建模联盟 (MSM) 活动将充分利用我们现有的 GOPC 和 PSC/CMU 资源和工作，这包括广泛的实地研究，以提供大量广泛的数据集，以帮助填充、校准和验证。 VPOP 并成立一个利益相关者工作组来指导 VPOP 开发、测试和实施。 具体目标 1 将开发 VPOP，这是一个可以生成代表六个肥胖相关量表的地理空间明确计算模型的平台。具体目标 2 将需要利用 VPOP 生成两个样本大都市区（巴尔的摩大都市区和纽约市）的多尺度模拟模型，用于确定整个地区儿童和成人肥胖的关键驱动因素。六个不同的尺度，并确定哪些因素可能对特定计划和政策最敏感。对于具体目标 3，我们将通过与城市政策制定者、卫生和规划部门等主要利益相关者合作，将 VPOP 生成的模型转化为决策。领导力、医疗保健管理人员和第三方付款人测试和优化一套特定的肥胖控制政策和干预措施。