EAGER: Development and Validation of Analytic Spatial-Temporal Models to Help Study and Mitigate the National Opioid-Heroin Co-Epidemic

美国正处于阿片类药物滥用和滥用的严重流行之中。根据卫生局局长2016年的报告“美国面临成瘾”，2014年有28,647人死于涉及某种阿片类药物的药物过量，包括处方止痛药、海洛因和芬太尼。报告指出，“个人、家庭和社区的累积成本是惊人的，是许多直接和间接影响的结果，包括损害身心健康、传染病传播增加、生产力下降、生活质量下降、犯罪和暴力增加、机动车碰撞增加、虐待和忽视儿童以及医疗保健费用。”该报告还认识到临床、业务和信息技术的进步以及医疗保健和刑事司法改革努力的潜力，以推动预防和治疗服务的改善。这一探索性研究早期概念补助金项目将探讨了解和缓解多种相互关联的阿片成瘾流行病的操作方法。这些方法的开发和评估将与政策制定者咨询小组的持续反馈一起进行，这些政策制定者包括为多个城市和农村人口服务的州卫生部门。这些新方法的潜在影响包括改进预防战略和支持在治疗和阻断之间有效分配资源。该项目还将培养几名工程学研究生和本科生，他们将能够帮助为当前威胁国家健康和安全的公共部门问题提供解决方案。该奖项将支持研究，以制定相互依赖的国家阿片类药物和海洛因疾病流行的高保真时空分析模型。S开发的模型将结合基于微分方程、细胞自动机和随机过程的方法，并将纳入不同的地理和社会网络拓扑，考虑地区和人口的异质性，并捕捉影响疾病传播动力学的行为特征。这些模型的一个重要方面是明确考虑了多种疾病模式之间的相互关系，包括诸如物质可获得性、成瘾进展、药物转换和可替代性、可变药物效力和市场(价格/供应/需求)力量等因素。这些模型将利用从当地和区域公共卫生机构获得的数据进行开发和验证。模型将由定性的人种学技术提供信息，这些技术描述了人与人之间和地区与地区之间的传播动态。这些模型将作为评估当前和未来干预战略的平台，预计将有助于为监督州公共卫生部门、治疗中心、社会服务机构和执法机构的资源分配的政策制定者提供信息。

The US is In the midst of a serious epidemic of opioid drug misuse and abuse. According to the Surgeon General's 2016 report, "Facing Addiction in America", in 2014, 28,647 people died from drug overdoses involving some type of opioid, including prescription pain relievers, heroin, and fentanyl. The report states that the "accumulated costs to the individual, the family, and the community are staggering and arise as a consequence of many direct and indirect effects, including compromised physical and mental health, increased spread of infectious disease, loss of productivity, reduced quality of life, increased crime and violence, increased motor vehicle crashes, abuse and neglect of children, and health care costs." The report also recognizes the potential for advances in clinical, operational, and informational technologies, coupled with health care and criminal justice reform efforts, to drive improvements in prevention and treatment services. This EArly-concept Grant for Exploratory Research (EAGER) project will address operational methods to understand and mitigate multiple interrelated opioid addiction epidemics. The methods will be developed and evaluated with ongoing feedback from an advisory group of policy makers, including state health departments serving multiple urban and rural populations. The potential impact of these new methods includes improved prevention strategies and support for effective allocation of resources between treatment and interdiction. The project will also educate several graduate and undergraduate engineering students who will be in a position to help provide solutions to current public sector issues that threaten the nation's health and security.This award will support research to formulate high fidelity spatiotemporal analytical models of the interdependent national opioid and heroin disease epidemics. The model(s) developed will combine approaches based on differential equations, cellular automata, stochastic processes and will incorporate different geographic and social network topologies, account for regional and population heterogeneity, and capture behavioral characteristics that influence dynamics of disease spread. An important aspect of these models is the explicit consideration of the inter-relationships between multiple disease modalities, including such factors as substance availability, addiction progression, drug switching and substitutability, variable drug potency, and market (price/supply/demand) forces. The models will be developed and validated using data obtained from local and regional public health agencies. Models will be informed by qualitative ethnographic techniques that describe the dynamics of person-to-person spread and region-to-region spread. These models will serve as platforms for the assessment of current and future intervention strategies, and are expected to help inform policy makers that oversee resource allocation in state public health departments, treatment centers, social service agencies, and law enforcement agencies.