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Data Science Approaches in Criminal Justice and Public Health Research: Lessons Learned From Opioid Projects

NCJ Number
Journal of Contemporary Criminal Justice Volume: 37 Issue: 2 Dated: 2021 Pages: 175-189
Date Published
17 pages

This paper provides a review of the authors’ research into epidemiological criminology and lays out the main benefits and challenges of adopting data science approaches for addressing the opioid epidemic through public health and safety partnerships, research, and policy.


The persistence of the nation’s opioid epidemic has called on criminal justice and public health agencies to collaborate more than ever. This epidemiological criminology framework highlights the surveillance of public health and safety, often using data science approaches, to inform best practices. The purpose of this article is to delineate the main benefits and challenges of adopting data science approaches for epidemiological criminology partnerships, research, and policy. The authors offer “lessons learned” from their opioid research in Delaware and Florida to advise future researchers, especially those working closely with policymakers and practitioners in translating science into impactful best practices. The paper begins with a description of the authors’ projects, pivots to the challenges they have faced in contributing to science and policy, and closes with recommendations for future research, public advocacy, and practice. Publisher Abstract Provided

Date Published: January 1, 2021