Detecting Opioid Distribution Networks Using Network Modeling and Community-Based Intelligence

• NCJ Number: 304102
• Date Published: February 2022
• Grant Number(s): 2017-IJ-CX-0017
• Agencies: NIJ
• Publication Type: Research (Applied/Empirical)

Annotation

This article explains how researchers who performed a study supported by the National Institute of Justice sought to find novel ways to characterize and ultimately inhibit opioid distribution networks through data-driven network analysis and the use of citizen intelligence.

Abstract

U.S. opioid-related overdose deaths have increased significantly in recent years, topping 49,860 in 2019. Pennsylvania has suffered a particularly high number of opioid-related (including illicit prescription drugs, fentanyl, and heroin) deaths in recent years. A study supported by the National Institute of Justice highlights the need for community-based intelligence in efforts to interrupt opioid distribution networks. The article explains how researchers who performed that study sought to find novel ways to characterize and ultimately inhibit opioid distribution networks through data-driven network analysis and the use of citizen intelligence. The researchers emphasize that supply reduction should be included as a tool in comprehensive substance responses and policies. Other recommendations include participatory mapping with local residents, law enforcement using network modeling and simulation techniques to enhance their investigations, and criminal justice administrative entities making efforts to connect locally derived data to extra-local sources.