A statistical analysis of drug seizures and opioid overdose deaths in Ohio from 2014 to 2018

Abstract

This paper examines the association between police drug seizures and drug overdose deaths in Ohio from 2014 to 2018. We use linear regression, ARIMA models, and categorical data analysis to quantify the effect of drug seizure composition and weight on drug overdose deaths, to quantify the lag between drug seizures and overdose deaths, and to compare the weight distributions of drug seizures conducted by different types of law enforcement (national, local, and drug task forces). We find that drug seizure composition and weight have strong predictive value for drug overdose deaths (F = 27.14, p < 0.0001, R^2 = .7799). A time series analysis demonstrates no statistically significant lag between drug seizures and overdose deaths or weight. Histograms and Kolmogorov-Smirnov tests demonstrate stark differences between seizure weight distributions of different types of law enforcement (p < 0.0001 for each pairwise comparison). We include a discussion of what our conclusions mean for law enforcement and harm reduction efforts.

This paper was published in 2021, and has been cited six times so far. We improved one of the models from the published version, and updated the bibliography