Modeling Legal Strategies for Opioid Harm Reduction in North Carolina

Abstract

Over the last decade, the widespread misuse of fentanyl greatly increased opioid overdose death rates across North Carolina. Treatment and prevention strategies varied widely by state, and we sought to study the impact of drug courts and what conditions can make their presence more or less effective. We were additionally interested in policing trends and race in the context of their impact on opioid misuse. We used Bayesian autoregressive Poisson log-linear models to estimate coefficients for various measurements of judicial and police activity. We found drug courts were meaningfully effective only in the presence of Democrat-affiliated district attorneys and produced better results in counties with fewer drug possession arrests when controlling for overall police activity. Additionally, we found the presence of drug courts are generally related to lesser racial disparities in overdose outcomes, with major exceptions. We conclude these courts serve as a valuable intervention and urge North Carolina prosecutors to continue their efforts to pivot from criminal to therapeutic models for victims of the opioid epidemic.

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arrests, Bayesian, courts, opioid overdose, Poisson autoregressive model, spatial random effect

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Wake Forest University