D-ISN: Improving our Understanding of Illegal Opioid Supply Networks

这一非法供应网络扰乱行动(D-ISN)项目的目的是通过研究芬太尼等危险非法合成阿片类药物的出现和假冒处方阿片类药物的兴起，更好地了解非法供应网络。该项目将通过解决全国范围内致命的药物过量流行问题来促进国民健康和福利。通过补充理论发展和将非法阿片市场与其他非法市场(如贩运人口、假冒产品、走私野生动物等)进行系统比较，该项目将查明并测试对最近出现的强力合成阿片类药物所引发的关键问题的解释。更好地了解供应商业务、贩运者决策和非法供应网络的经济基础，将有助于指导旨在破坏供应的有效政策反应。对于阿片类药物，供应商决策的系统特征可以提供宝贵的经验教训，以减少危害。将阿片类药物与其他非法供应网络的发现进行对比，可能会在一系列贩运领域提供更多的见解。该项目将借鉴经济学、运筹学、计算机科学和社会科学的方法，以解决三个主要目标：(1)通过网上抓取合成阿片类药物的在线清单，审查联邦法院关于合成阿片类药物贩运的文件，并与参与打击合成阿片贩运的执法部门进行访谈，收集和分析与非法供应合成阿片类药物有关的新数据；(2)扩大现有的非法市场理论框架，从风险和价格出发，最好地解释与芬太尼非法分销相关的模式；以及(3)通过起草与其他违禁品贸易方面的外部专家的比较卷，综合不同非法商品网络的调查结果。数据收集将利用自动化软件工具、自然语言处理和半结构化访谈。经济和供应链建模将用于解释数据和制定结果。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The objective of this Disrupting Operations of Illicit Supply Networks (D-ISN) project is to better understand illicit supply networks by studying the emergence of dangerous illegal synthetic opioids, such as fentanyl, and the rise of counterfeit prescription opioid medications. The project will advance the national health and welfare by addressing a nationwide epidemic of fatal drug overdoses. Through complementary theory development and systematic comparison of illegal opioid markets with other illegal markets (e.g., human trafficking, counterfeit products, wildlife smuggling, etc.), the project will identify and test explanations for key questions prompted by the recent emergence of potent synthetic opioids. An improved understanding of supplier operations, trafficker decision-making, and economic foundations of illegal supply networks will help guide effective policy responses aimed at disrupting supply. For opioids, systematic characterization of supplier decision-making can offer valuable lessons to reduce harms. Contrasting findings for opioids with those for other illegal supply networks may offer additional insights across a range of trafficking domains.This project will draw on methods from economics, operations research, computer science, and social sciences to address three major aims: (1) collect and analyze new data related to the illegal supply of synthetic opioids through web-scraping of online listings for these drugs, reviewing federal court documents for trafficking in synthetic opioids, and conducting interviews with law enforcement involved in countering synthetic opioid trafficking; (2) expand existing theoretical frameworks of illegal markets derived from risks and prices to best explain the patterns associated with the illegal distribution of fentanyl; and (3) synthesize findings across networks for different illicit commodities through the drafting of comparative volumes with external experts in trade in other contraband. Data collection will leverage automated software tools, natural language processing, and semi-structured interviews. Economic and supply chain modeling will be used to interpret data and formulate findings.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.