Behavioral Epidemiology: Applications of Agent-Based Modeling to Infectious Disea

行为流行病学：基于主体的建模在传染病中的应用

• 批准号: 7915229
• 负责人: Joshua M. Epstein
• 金额: $ 82万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-30 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7915229
• 关键词: Archaeology; Area; Behavior; Behavioral; Behavioral Mechanisms; Books; Chronic Disease; Communicable Diseases; Communication; Communities; Computer Simulation; Containment; Defect; Disasters; Disease; Disease Outcome; Economics; Employee Strikes; Epidemic; Epidemiology; Feedback; Fright; Goals; Government; Health; Individual; Influenza; Modeling; Obesity; Outcome; Panic; Prevention strategy; Public Health; Readiness; Research; Risk; Role; Shapes; Smallpox; Social Sciences; Stress; Techniques; Vaccines; Violence; Work; abstracting; base; design; innovation; non-compliance; pandemic influenza; peer; social

PI: Dr. Joshua M. Epstein Title: Behavioral Epidemiology: Applications of Agent-Based Modeling to Infectious Diseases, Chronic Diseases, and Disaster Preparedness Abstract: Models are central in important areas of public health, including pandemic flu, chronic disease, and disaster preparedness. However, behavioral factors are virtually ignored in current modeling, a crucial defect. Behavior can fundamentally shape the spread of infectious diseases (such as influenza). People may flout, or not know, government containment directives. Distrustful communities may refuse vaccine. Rather than self-isolate, exposed individuals may flee in fear, accelerating the spatial spread of disease. Epidemic modeling to date has virtually ignored these behavioral adaptations and their consequences. Behavior also shapes chronic disease outcomes-yet no behavioral mechanism is currently offered to explain, for example, the striking historical dynamics of obesity. Theoretical and empirical work could identify such mechanisms, including peer effects. Behavior would also shape health outcomes in a disaster. In an urban toxic plume release, the natural impulse to flee could amplify congestion, undermining evacuation, and increasing exposure. Are there simple decentralized rules or tailored messages that could, instead, generate efficient evacuation? Behavior under stress may be based on poor information, unwarranted fear, or entrenched social norms. These possibilities should condition risk communication and the design of containment/preventive strategies across the spectrum of public health threats. At present, they do not. A central goal of this research, then, is to model boundedly rational endogenous behavioral adaptations and their feedback effects on spatio-temporal disease dynamics. The Project covers both the epidemiology of behaviors (such as panic, non-compliance, distrust) and the role of behavioral factors in the progress of infectious and chronic diseases. The core analytical technique will be agent-based modeling by multi- disciplinary research teams. The PI is a recognized pioneer in this innovative field, and has directed successful multi-disciplinary agent modeling projects on Smallpox, Archaeology, Economics, and Civil Violence, as recounted in his book, Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton, 2006).

PI：约书亚博士M.爱泼斯坦 行为流行病学：基于代理的建模应用于 传染病、慢性病和灾害准备 摘要： 模型是公共卫生重要领域的核心，包括大流行性流感， 慢性病和灾难准备。然而，行为因素 在目前的模型中几乎被忽略了，这是一个关键的缺陷。行为可以 从根本上塑造传染病（如流感）的传播。人 可能会无视或不知道政府的遏制指令不信任 社区可能会拒绝接种疫苗。而不是自我孤立，暴露的个人 可能会因恐惧而逃离，加速疾病的空间传播。流行病建模， 事实上，戴特忽略了这些行为适应及其后果。 行为也影响慢性病的预后，但没有行为机制 例如，目前提供的解释， 肥胖理论和经验工作可以确定这种机制， 包括同伴效应。行为也会影响灾难中的健康结果。 在城市有毒羽流释放时，逃离的自然冲动可能会放大 拥挤，破坏疏散，增加暴露。有没有简单的 去中心化的规则或定制的信息， 疏散？压力下的行为可能是基于不良信息， 毫无根据的恐惧或根深蒂固的社会规范。这些可能性应该 条件风险沟通和遏制/预防的设计 应对各种公共卫生威胁的战略目前，他们没有。 本研究的一个中心目标是建立有限理性内生模型 行为适应及其对时空疾病的反馈作用 动力学该项目涵盖了行为的流行病学（如恐慌， 不遵守，不信任）和行为因素在进展中的作用， 传染病和慢性病。 核心分析技术将是基于多Agent的建模， 学科研究团队。PI是这一创新领域公认的先驱 领域，并指导了成功的多学科代理建模项目， 正如他在书中所述，天花、考古学、经济学和民间暴力， 生成社会科学：基于Agent的计算建模研究 （普林斯顿，2006年）。