Abstract: Ohio is one of the states most impacted by the opioid epidemic and experienced the second highest age-adjusted fatal drug overdose rate in 2017. Initially it was believed prescription opioids were driving the opioid crisis in Ohio. However as the epidemic evolved, opioid overdose deaths due to fentanyl have drastically increased. In this work, we develop a Bayesian multivariate spatio-temporal model for Ohio county overdose death rates from 2007 to 2018 due to different types of opioids. The log-odds are assumed to follow a spatially varying change point regression model. By assuming the regression coefficients are a multivariate conditional autoregressive process, we capture spatial dependence within each drug type and also dependence across drug types. The proposed model allows us to not only study spatio-temporal trends in overdose death rates, but also to detect county-level shifts in these trends over time for various types of opioids.

Dr. Staci Hepler is originally from southern Ohio and earned a Bachelor's degree in Mathematics Education from Shawnee State University in 2010 before going on to earn a PhD in Statistics from The Ohio State University. In 2015 Staci joined the faculty in the Department of Mathematics and Statistics at Wake Forest University in Winston-Salem, NC. Her primary research interests are in applied spatio-temporal statistics and Bayesian modeling, and she focuses on problems in public health, ecology, and environmental science.