Counterdrug interdiction efforts designed to seize or disrupt cocaine shipments between South American source zones and US markets remain a core US “supply side” drug policy and national security strategy. However, despite a long history of US-led interdiction efforts in the Western Hemisphere, cocaine movements to the United States through Central America, or “narco-trafficking,” continue to rise. Here, we developed a spatially explicit agent-based model (ABM), called “NarcoLogic,” of narco-trafficker operational decision making in response to interdiction forces to investigate the root causes of interdiction ineffectiveness across space and time. The central premise tested was that spatial proliferation and resiliency of narco-trafficking are not a consequence of ineffective interdiction, but rather part and natural consequence of interdiction itself. Model development relied on multiple theoretical perspectives, empirical studies, media reports, and the authors’ own years of field research in the region. Parameterization and validation used the best available, authoritative data source for illicit cocaine flows. Despite inherently biased, unreliable, and/or incomplete data of a clandestine phenomenon, the model compellingly reproduced the “cat-and-mouse” dynamic between narco-traffickers and interdiction forces others have qualitatively described. The model produced qualitatively accurate and quantitatively realistic spatial and temporal patterns of cocaine trafficking in response to interdiction events. The NarcoLogic model offers a much-needed, evidence-based tool for the robust assessment of different drug policy scenarios, and their likely impact on trafficker behavior and the many collateral damages associated with the militarized war on drugs.
Long‐standing federal drug‐control policy aims to reduce the flow of narcotics into the USA, in part by intercepting cocaine shipments en route from South American production regions to North American consumer markets. Drug interdiction efforts operate over a large geographic area, containing complex drug trafficking networks in a dynamic environment. The extant interdiction models in the operations research and location science literature do not realistically model the objectives of and constraints on the interdiction forces, and therefore counterdrug organizations do not employ those models in their decision‐making processes. This article presents three new models built on the maximal covering location problem (MCLP): the maximal covering location problem for interdiction (MCLP‐I), multiple‐demand maximal covering location problem (MD‐MCLP), and multiple‐type maximal covering location problem (MT‐MCLP). These are novel formulations that permit multiple types of demands and facilities to be covered, and the utility of these formulations is demonstrated in the context of counterdrug operations. Optimal interdiction locations are determined within the geography of the Central American transit zone, using a coupled GIS and optimization framework. The results identify the optimal interdiction locations for known or estimated drug shipments and can constrain those optimal locations by differentiating among drug traffickers, the types of interdiction resources, and agency jurisdictions. This research both demonstrates the flexibility in designing alternative interdiction scenarios and presents novel covering models that may be extended to other application areas and operational contexts.
more » « less- NSF-PAR ID:
- 10445255
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Transactions in GIS
- Volume:
- 26
- Issue:
- 4
- ISSN:
- 1361-1682
- Page Range / eLocation ID:
- p. 1962-1980
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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