All ETDs from UAB

Advisory Committee Chair

Karen Cropsey

Advisory Committee Members

Grant Drawve

Burel Goodin

Brandi McCleskey

Sylvie Mrug

Jeffery T Walker

Document Type


Date of Award


Degree Name by School

Doctor of Philosophy (PhD) College of Arts and Sciences


Fatal drug overdoses are now the leading cause of accidental death in the U.S., responsible for over 107,600 deaths in 2021. Since 2000 the rate of overdose fatalities has increased over 140%. This epidemic has been particularly impactful in rural areas as from 2006-2016, the rural overdose death rate surpassed those in urban areas. Geospatial analytics provide an effective strategy for identifying profiles and patterns in the spatial distribution of overdose locations as well as geographic and demographic variables that associate with overdose occurrences. Furthermore, predictive risk modeling platforms allow for the identification of anticipated overdose hotspots across a geography such as a county, city, or census tract. The current proposal will assess medical examiner verified overdose fatalities throughout the state of Ohio from 2016-2018. Ohio was selected due to its above-national overdose rates and excellent public health and criminal justice data. Overdoses will be examined at the state, county, and point-specific levels. The specific aims of this proposal are to 1) compare the profiles of overdoses occurring in rural and urban areas across the state by examining classes of variables that have been shown to associate with overdose including socioeconomic data obtained from the U.S. Census Bureau, decedent characteristics, and toxicology results; 2) Build predictive models using Risk Terrain Modeling to examine the relationship between overdose locations and point-specific factors including criminal incidents and features of the built environment. These models will focus on the two urban and rural counties with the highest rates of overdose; and 3) Evaluate the predictive efficacy of Risk Terrain Models by comparison to other risk forecasting methodologies such as Kernel Density Estimation and Random Forest. The goal of this proposal is to create a replicable, cost-effective framework to accurately anticipate future overdoses and inform the placement of substance use and overdose prevention resources. This will be accomplished by utilizing publicly available data in unison with state-gathered mortality data to address a public health need.

Available for download on Friday, May 09, 2025