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

这一破坏非法供应网络行动(D-ISN)项目将通过提高对毒品和性贩运网络的了解，发现其运作模式，并建立扰乱其活动的机制，来加强国家公共安全、健康和福利。人口贩运和非法毒品在美国是无处不在的问题，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，打击这些问题需要面对多重挑战，其中包括分散的数据、多个代理人、市场和贩运者的适应能力以及隐藏的行动。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。这是通过与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。该研究计划将重点放在美国西南部，那里的主要城市地区有街头卖淫踪迹，强劲的在线色情广告市场，以及活跃的帮派和毒品分销网络。这个项目产生的结构化数据库将向研究界公开提供。该项目采用多尺度方法，利用定性和定量方法，在宏观和微观层面分析和制定干预措施。该研究计划包括一个非法网络发现部分，以利用与幸存者和侦探的访谈、警察案件记录和非常规数据库中的背景数据构建非法供应网络。这将使系统地记录受害者流动、毒品流动、金融活动、交通枢纽的使用，以及这些活动是如何相互联系的。宏观分析提供了一种方法，用以描述参与非法网络行动的行为者、地点和金融工具之间的相互依存关系。该分析将复杂的相互依存关系提炼成可分析处理的逻辑关系，以设计能够挫败非法活动的组织、财务和地理战略。微观构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范围内设计干预措施。该项目开发了新的数学规划模型来推断交通热门路线，这些路线是预测的、高密度的交通路线。它还包括热路线中断的博弈论框架。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。

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.