D-ISN: TRACK 1: A Holistic Approach to Discovery, Modeling, and Interdiction of Drug and Human Trafficking Networks in the U.S. Southwest

这一打击非法供应网络项目将加强对毒品和性贩运网络的了解，发现其运作模式，并制定破坏其活动的机制，从而加强国家公共安全、健康和福利。人口贩运和非法毒品是美国普遍存在的问题，对医疗保健、社会服务和刑事司法基础设施产生了不可估量的负面影响。由于贩运活动的性质，包括数据分散、代理人多、市场和贩运者的适应性以及隐蔽行动，打击这些问题面临多重挑战。为了应对这些挑战，该项目整合了学术界、领域专家和执法机构的专业知识。这是通过侦探和幸存者的严格实地工作，以及社会科学、运筹学、计算机科学和信息科学的分析方法来实现的。该研究计划的重点是美国西南部，那里的主要城市地区有街头卖淫的踪迹、强大的网络性广告市场、活跃的帮派和毒品分销网络。这个项目产生的结构化数据存储库将对研究社区公开可用。该项目采用多尺度方法，在宏观和微观层面分析和制定干预措施，同时利用定性和定量方法。该研究计划包括一个非法网络发现组件，从幸存者和侦探的访谈、警方案件记录和非常规数据库的背景数据中构建非法供应网络。这将有助于系统地记录受害者的流动、毒品的流动、金融活动、交通枢纽的使用以及这些活动如何相互联系。宏观层面的分析提供了一种方法来描述参与非法网络操作的行动者、地点和金融工具之间的相互依赖性。该分析将复杂的相互依赖关系提炼为易于分析的逻辑关系，以便设计能够挫败非法活动的组织、财务和地理战略。微观层面的组成部分支持从执法和社会服务的角度在更精细和战术的地理尺度上设计干预措施。该项目开发了新的贩运热点路线推理数学规划模型，用于预测高密度的贩运路线。它还包括一个热门路线中断的博弈论框架。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This Disrupting Operations of Illicit Supply Networks (D-ISN) project will enhance national public safety, health, and welfare by improving the understanding of drug and sex trafficking networks, detecting their operational patterns, and developing mechanisms to disrupt their activities. The trafficking of humans and illicit drugs are pervasive problems in the United States, with immeasurable negative impacts on healthcare, social services, and criminal justice infrastructures. Combating these problems entails multiple challenges due to the nature of trafficking operations, which include scattered data, multiple agents, adaptability of both the market and traffickers, and hidden operations. To tackle these challenges, this project integrates expertise from academia, domain experts, and law enforcement agencies. This is achieved through rigorous field work with detectives and survivors, and methods of analysis from social sciences, operations research, computer science, and information science. The research plan focuses on the U.S. Southwest, whose main urban areas have street prostitution tracks, robust online sex advertisement markets, and active gang and drug distribution networks. The structured data repository resulting from this project will be publicly available to the research community.This project employs a multi-scale approach that analyzes and develops interventions at macro- and micro-levels, leveraging both qualitative and quantitative methods. The research plan includes an illicit network discovery component to construct illicit supply networks out of contextual data from interviews with survivors and detectives, police case records, and nonconventional databases. This will allow for the systematic documentation of victim movement, drug movement, financial activity, use of transportation hubs, and how these are interconnected. The macro-level analysis provides a methodology to characterize the interdependency between actors, locations, and financial instruments involved in the illicit network operation. The analysis distills complex interdependencies into analytically tractable logical relationships for the design of organizational, financial, and geographical strategies that can thwart illicit activities. The micro-level component supports the design of interventions from law enforcement and social service perspectives at a finer and tactical geographical scale. The project develops new mathematical programming models for the inference of trafficking hot routes, which are predicted, high-density trafficking routes. It also includes a game theoretical framework for the disruption of hot routes.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.