D-ISN/Collaborative Research: Mitigating the Harm of Fentanyl through Holistic Demand/Supply Interventions and Equitable Resource Allocations

D-ISN/合作研究：通过整体需求/供应干预和公平资源分配减轻芬太尼的危害

• 批准号: 2240359
• 负责人: Rakesh Nagi
• 金额: $ 51.65万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2027-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2240359&HistoricalAwards=false
• 关键词: ISN; Collaborative; Research; Mitigating; Harm

The objective of this Disrupting Operations of Illicit Supply Networks (D-ISN) research project is to investigate advanced methods and tools to mitigate the harm caused by the distribution and use of illicit opioids in the U.S. The project seeks to reduce the harm caused by illicit opioids by developing methods to study interventions on both the supply-side (by studying the supply chain of opioids) and demand-side (by shifting user pathways towards recovery) and to provide effective resource allocation between these different approaches. The convergent research agenda, augmented with collaboration from multiple community organizations, from courts, law enforcement, to public health, will integrate methods from criminology, public health, and operations research. This research will help to improve our understanding of the operations of illicit opioid supply chains, especially how fentanyl and its analogs find their way into other drugs and how to prevent their flow to users. On the demand-side, the project will enhance understanding of the impact of harm reduction strategies through user pathways to addiction. Overall, the project aims to improve the equitable and optimal allocation of demand- and supply-side intervention resources to mitigate the harm caused by illegal opioid use. The project advances and integrates multidisciplinary methods from product design, production, distribution, graph/network theory, optimization, data science, machine learning, agent-based simulation, and fair allocation to reduce harm caused by fentanyl and illicit opioids. The project has three main thrusts. First, the project investigates supply-Side disruptions through understanding the intersections of fentanyl and other Illicit opioid products and distribution networks. This thrust employs a Bill-Of-Materials perspective on product adulteration, transfer learning between licit and/or Illicit supply chains to fill-in data gaps and understanding and modeling the distribution network with multi-commodity flow disruption models for harm reduction. Secondly, the project studies demand-side interventions for different fentanyl user groups. This thrust comprises an investigation of opioid users’ motivations and pathways to use illicit opioids/fentanyl through semi-structured interviews and surveys, fentanyl dispersion in communities, and agent-based models of drug use and harm reduction strategies. The third thrust develops resource allocation models to study the effects of interventions, law-enforcement, and medication-assisted treatments through simulation modeling. The project will make use of definitions of harm, equity, and fairness in distribution of interventions/resources across socioeconomic groups, and new holistic optimization, and simulation models to bring together demand-side and supply-side decisions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该“扰乱非法供应网络运作”(D-ISN) 研究项目的目的是研究先进方法和工具，以减轻美国境内非法阿片类药物的分销和使用造成的危害。该项目旨在减少非法阿片类药物造成的危害通过开发方法来研究供应方（通过研究阿片类药物的供应链）和需求方（通过将用户途径转向恢复）的干预措施，并在这些不同方法之间提供有效的资源分配。议程，加上法院、执法部门和公共卫生等多个社区组织的合作，将整合犯罪学、公共卫生和运筹学的方法。这项研究将有助于提高我们对非法阿片类药物供应链运作的了解。特别是芬太尼及其类似物如何进入其他药物以及如何防止其流入使用者手中，该项目将通过使用者成瘾途径增强对减少伤害策略的影响的了解。改善资源的公平优化配置该项目推进并整合了产品设计、生产、分销、图/网络理论、优化、数据科学、机器学习、基于代理的模拟等多学科方法。和公平分配，以减少芬太尼和非法阿片类药物造成的危害 该项目有三个主要目标：首先，该项目通过了解芬太尼和其他非法阿片类药物产品和分销网络的交叉点来调查供应方中断。从材料清单角度了解产品掺假、合法和/或非法供应链之间的转移学习以填补数据空白，以及使用多商品流动中断模型来理解和建模分销网络以减少危害。 其次，该项目研究需求。 - 针对不同芬太尼使用者群体的侧面干预措施包括通过半结构化访谈和调查、芬太尼在社区中的分散以及基于代理的方式调查阿片类药物使用者使用非法阿片类药物/芬太尼的动机和途径。第三个重点是开发资源分配模型，通过模拟建模来研究干预措施、执法和药物辅助治疗的效果。跨社会经济群体的干预措施/资源分配，以及新的整体优化和模拟模型，以汇集需求方和供应方的决策。该奖项的法定使命，并通过使用基金会的智力优点和更广泛的评估，被认为值得支持影响审查标准。