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Oklahoma Methamphetamine Data Initiative

Award Information

Award #
2020-R2-CX-0014
Funding Category
Competitive Discretionary
Location
Congressional District
Status
Closed
Funding First Awarded
2020
Total funding (to date)
$587,219

Description of original award (Fiscal Year 2020, $587,219)

The proposed Oklahoma Methamphetamine Data Initiative (OMDI) will analyze national and local drugs and crime data to examine methamphetamine (meth)-related violent and other crime trends and inform narcotics law enforcement intervention strategies. The partnership between the School of Forensic Sciences and the Department of Psychiatry and Behavioral Sciences is supported by state, local, and tribal agencies. OMDI goals are to: establish procedures and metrics to evaluate the relationship between meth and violent crime; identify static and dynamic factors associated with violent crime stemming from meth use or distribution to improve community surveillance in Oklahoma; develop a regularly updated dashboard for law enforcement prevention/intervention deployment; and demonstrate the utility of this model for other states, rural areas, and Indian Country. Research questions include: where are meth use and violent crime intersections more prevalent; are there cultural and geographic differences (e.g., American Indian and rural communities); are there upstream factors (socio-environmental factors) that mediate violent crime; and does identifying patterns in traditional and new data aid community surveillance, intervention, and prevention? The cross-sectional and longitudinal research design leverages data to correlate and forecast meth-related violent crime. These include CDC’s WONDER data on drug overdoses and Behavioral Risk Factor Surveillance System (BRFSS), FBI’s National Incident Based Reporting System (NIBRS) on crimes, the Oklahoma State Courts Network (OSCN) on criminal cases, and Google Trends data on meth-related searches. Data will be extracted using a publicly available application-programming interface and a new Graphic User Interface. Statistical techniques include hierarchical regression, structural equation modeling, and time series models. Dissemination will be via medical, forensic, criminal justice, and police publications and conferences, and federal, state, and local law enforcement briefings. Note: This project contains a research and/or development component, as defined in applicable law, and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14). CA/NCF

Date Created: September 16, 2020