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Identifying and Informing Strategies for Disrupting Drug Distribution Networks: An Application to Opiate Flows in Pennsylvania

NCJ Number
Glenn Sterner; Ashton Verdery; Shannon Monnat; Scott Yabiku; Gary Zajac; Peter Forster; Danielle Rhubart,; Sam Nur
Date Published
39 pages

This is the Final Report of a project that examined the structure of local opioid distribution networks and markets in Pennsylvania, with attention to the capacity for local intelligence to disrupt local opioid supply networks and markets.


An interdisciplinary team of researchers worked with the Pennsylvania State Police (PSP) to identify locations in the state where it would be possible to detect and assess opioid distribution networks and markets and obtain local intelligence on drug-related activity. Based on data provided by the PSP and other sources, researchers constructed observed and modeled opioid networks in six target counties. Existing software (“HarvestMapper”) was modified to enable users to identify locations of drug-related activity in communities through participatory mapping on touchscreen laptops. These locations were compared to known drug activities through data provided by the PSP. Results indicate that community-based intelligence captured through electronic participatory mapping has the potential to inform investigations into local drug activity. The locations identified by residents matched official records; and, in some cases, identified additional locations that could be of interest to law enforcement in disrupting local drug markets. The software could be developed to assist law enforcement in collecting critical intelligence data. Results from network modeling indicate that local opioid distribution networks are mostly organized by substance, with a few individuals distributing multiple types of substances. Also, using the observed data from drug-related cases, researchers were able to simulate unobserved connections that may be more difficult to capture through intelligence-based investigations alone. This has promise to inform new strategies and techniques for supply disruptions at the local level. Four recommendations are offered for advancing data-driven, intelligence-led approaches for supply disruption of opioids that could also inform other substance distribution network disruption. 12 tables, 7 figures, and 61 references