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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.

 

Despite more than 40 years of counterdrug interdiction efforts in the Western Hemisphere, cocaine trafficking, or ‘narco-trafficking’, networks continue to evolve and increase their global reach. Counterdrug interdiction continues to fall short of performance targets due to the adaptability of narco-trafficking networks and spatially complex constraints on interdiction operations (e.g., resources, jurisdictional). Due to these dynamics, current modeling approaches offer limited strategic insights into time-varying, spatially optimal allocation of counterdrug interdiction assets. This study presents coupled agent-based and spatial optimization models to investigate the co-evolution of counterdrug interdiction deployment and narco-trafficking networks’ adaptive responses. Increased spatially optimized interdiction assets were found to increase seizure volumes. However, the value per seized shipment concurrently decreased and the number of active nodes increased or was unchanged. Narco-trafficking networks adaptively responded to increased interdiction pressure by spatially diversifying routes and dispersing shipment volumes. Thus, increased interdiction pressure had the unintended effect of expanding the spatial footprint of narcotrafficking networks. This coupled modeling approach enabled the study of narco-trafficking network evolution while being subjected to varying interdiction pressure as a spatially complex adaptive system. Capturing such co-evolution dynamics is essential for simulating traffickers’ realistic adaptive responses to a wide range of interdiction scenarios. 

Illicit supply networks (ISNs) are composed of coordinated human actors that source, transit, and distribute illicitly traded goods to consumers, while also creating widespread social and environmental harms. Despite growing documentation of ISNs and their impacts, efforts to understand and disrupt ISNs remain insufficient due to the persistent lack of knowledge connecting a given ISN’s modus operandi and its patterns of activity in space and time. The core challenge is that the data and knowledge needed to integrate it remain fragmented and/or compartmentalized across disciplines, research groups, and agencies tasked with understanding or monitoring one or a few specific ISNs. One path forward is to conduct comparative analyses of multiple diverse ISNs. We present and apply a conceptual framework for linking ISN modus operandi to spatial-temporal dynamics and patterns of activity. We demonstrate this through a comparative analysis of three ISNs – cocaine, illegally traded wildlife, and illegally mined sand – which range from well-established to emergent, global to domestic in geographic scope, and fully illicit to de facto legal. The proposed framework revealed consistent traits related to geographic price structure, value capture at different supply chain stages, and key differences among ISN structure and operation related to commodity characteristics and their relative illicitness. Despite the diversity of commodities and ISN attributes compared, social and environmental harms inflicted by the illicit activity consistently become more widespread with increasing law enforcement disruption. Drawing on these lessons from diverse ISNs, which varied in their histories and current sophistication, possible changes in the structure and function of nascent and/or low salience ISNs may be anticipated if future conditions or law enforcement pressure change. 

Among geographers, recent focus on the illicit and illegal has tended to fall into two camps. Economic geographers focus on regimes of illicitness and corresponding production of specific forms of economic space; political ecologists and land change scholars, on the other hand, scrutinised how illicit commodity flows shape land and resource use, especially in the global South. This paper offers an initial integration of these two relatively separate subfields, specifically in terms of their complementary attention to uneven development. We use the concept of “global commodity chains” to explore the ways in which the regulation of agricultural commodities shapes how they are trafficked and embed in space, with particular attention to sites of international transshipment. When a commodity is illegal, spaces of transit take on significant analytical importance. As a heuristic, we present a comparative mapping of two agricultural commodity chains linking Colombia and the USA: coffee and cocaine. Their comparison highlights how “illicitness” fundamentally transforms cocaine’s spatiality, requiring risk evasion that results in characteristically enlarged transit spaces and huge differentials between producer and consumer price. We show how rents circulate in those transit spaces, socially and ecologically embedding in diffuse, fluid networks with severe consequences for people and environments. We conclude with implications for work on illicit commodities and the collateral social and environmental harms they produce.