Geospatial Analytics with Drug Arrest Data (014)


Study Information

The University of Maryland’s Center for Substance Abuse Research (CESAR) established the Coordinating Center for the National Drug Early Warning System (NDEWS) for NIDA in 2014. NDEWS is a public health surveillance system that generates critically needed information about drugs and their public health consequences so that rapid, informed, and effective public health responses can be developed. Over the past four years, the Coordinating Center has developed national and international collaborations to support the ability to identify, monitor, and follow-up on emerging drugs and changing drug trends. These capabilities will be used in studies to link scientists and practitioners from the justice and public health fields and to generate resources and tools to support improvements in both fields.

This administrative supplement will help expand collaboration with the DEA to provide interactive National Forensic Laboratory Information System (NFLIS) data for U.S. states for 2007-2016. The provided information will include state counts of the most frequently identified drugs, fentanyl and fentanyl-related substances, synthetic cannabinoids, and synthetic cathinones. NDEWS will create customized graphics and innovative data visualization products that will facilitate state, regional, and national analysis of emerging opioid availability in the U.S.

This supplement will also help expand collaboration with the University of Maryland’s Center for Geospatial Information Science to conduct geospatial analytics with drug arrest data and geospatial characteristics to assess availability and access to OUD services. The geospatial analyses conducted will provide recommendations for local program planners for locations of future OUD services such as mobile clinics. Ultimately, results will be used in the development of a predictive model for sites without easily accessible data.

Study Team

PI: Eric Wish, Erin Artigiani, Kathleen Stewart

umd logo

Research Type

Accelerator Supplement, Modeling Project