D-ISN: TRACK 1: Illicit Drug Trafficking Networks: Behavioral Responses to Interdiction

D-ISN：轨道 1：非法毒品贩运网络：对拦截的行为反应

• 批准号: 2039975
• 负责人: Kevin Curtin
• 金额: $ 74.64万
• 依托单位: University of Alabama Tuscaloosa
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2039975&HistoricalAwards=false
• 关键词: ISN; TRACK; Illicit; Drug; Trafficking

This Disrupting Operations of Illicit Supply Networks (D-ISN) project promotes scientific understanding of illicit supply networks by providing insight into the ways Central American cocaine trafficking networks adapt to US-led counterdrug interdiction operations attempting to disrupt them. By offering an interdisciplinary understanding of the environment in which interdiction forces operate in the Central American transit zone between South American sources and U.S. markets, this research ascertains the structure and function of cocaine supply networks, as well as how they transform in response to interdiction efforts. This project engages with U.S. government agencies and military organizations charged with disrupting these illicit supply networks, and it contributes to national and hemispheric security.This project investigates the adaptive behaviors of cocaine trafficking networks in response to varied interdiction strategies within the transit zone of Central America and associated maritime areas. The research leverages data science analytical techniques and GIS systems in combination with a modeling approach that identifies traffickers’ behavioral tendencies for relocating existing trafficking routes, creating new routes, and/or shifting cocaine conveyance methods in response to interdiction operations. In doing so, this project establishes convergence among operations engineering, geographic, data science, and criminological perspectives, leading to comparative analyses of the dynamic and adaptive interactions between illicit supply networks and law enforcement interventions.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.

这个非法供应网络（D-ISN）项目的破坏行动，促进了对非法供应网络的科学理解，提供了深入了解中美洲可卡因贩运网络适应美国领导的禁毒行动试图破坏他们的方式。通过提供一个跨学科的环境中，阻截部队在南美来源和美国市场之间的中美洲过境区的运作的理解，本研究的可卡因供应网络的结构和功能，以及他们如何转变，以响应阻截的努力。该项目与负责破坏这些非法供应网络的美国政府机构和军事组织合作，为国家和半球安全做出贡献。该项目调查了中美洲过境区和相关海域内可卡因贩运网络对各种拦截策略的适应行为。该研究利用数据科学分析技术和GIS系统，结合建模方法，确定贩运者的行为倾向，以重新定位现有贩运路线，创建新路线和/或改变可卡因运输方法以应对拦截行动。在此过程中，该项目在运营工程、地理、数据科学和犯罪学视角之间建立了融合，从而对非法供应网络和执法干预之间的动态和适应性互动进行了比较分析。该奖项反映了NSF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。

项目成果

Shifting landscape suitability for cocaine trafficking through Central America in response to counterdrug interdiction

为应对反毒品拦截，改变中美洲可卡因贩运的景观适宜性

• DOI: 10.1016/j.landurbplan.2022.104359
• 发表时间: 2022
• 期刊: Landscape and Urban Planning
• 影响因子: 9.1
• 作者: Magliocca, Nicholas R.;Summers, Diana S.;Curtin, Kevin M.;McSweeney, Kendra;Price, Ashleigh N.
• 通讯作者: Price, Ashleigh N.

Comparative Analysis of Illicit Supply Network Structure and Operations: Cocaine, Wildlife, and Sand

• DOI: 10.31389/jied.76
• 发表时间: 2021-10
• 期刊: Journal of Illicit Economies and Development
• 作者: N. Magliocca;A. Torres;Jared D. Margulies;K. McSweeney;Inés Arroyo-Quiroz;N. Carter;Kevin M. Curtin;Tara Easter;Meredith L. Gore;Annette Hübschle;Francis Massé;Aunshul Rege;Elizabeth Tellman

Intersecting security, equity, and sustainability for transformation in the Anthropocene

人类世转型中安全、公平和可持续性的交叉

• DOI: 10.1016/j.ancene.2023.100396
• 发表时间: 2023
• 期刊: Anthropocene
• 影响因子: 3.6
• 作者: Magliocca, Nicholas R.

Spatialising illicit commodity chains: Comparing coffee and cocaine

非法商品链的空间化：咖啡和可卡因的比较

• DOI: 10.1111/area.12724
• 发表时间: 2021
• 期刊: Area
• 影响因子: 2.2
• 作者: Dávila, Anayansi;Magliocca, Nicholas;McSweeney, Kendra;Rueda, Ximena
• 通讯作者: Rueda, Ximena

Coupling agent-based simulation and spatial optimization models to understand spatially complex and co-evolutionary behavior of cocaine trafficking networks and counterdrug interdiction

基于耦合剂的模拟和空间优化模型，以了解可卡因贩运网络和反毒品拦截的空间复杂性和共同进化行为

• DOI: 10.1080/24725854.2022.2123998
• 发表时间: 2022
• 期刊: IISE Transactions
• 影响因子: 2.6
• 作者: Magliocca, Nicholas R.;Price, Ashleigh N.;Mitchell, Penelope C.;Curtin, Kevin M.;Hudnall, Matthew;McSweeney, Kendra
• 通讯作者: McSweeney, Kendra