An Integrated Abundance Model for Estimating County-Level Prevalence of Opioid Misuse in Ohio

Dr. Staci Hepler
Associate Professor of Statistics
Wake Forest University in Winston-Salem, North Carolina
Professor Sheng Jiang

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Description:  Opioid misuse is a national epidemic and a significant drug related threat to the United States. While the scale of the problem is undeniable, estimates of the local prevalence of opioid misuse are lacking, despite their importance to policy-making and resource allocation. This is due, in part, to the challenge of directly measuring opioid misuse at a local level. In this paper, we develop a Bayesian hierarchical spatio-temporal abundance model that integrates indirect county-level data on opioid-related outcomes with state-level survey estimates on prevalence of opioid misuse to estimate the latent county-level prevalence and counts of people who misuse opioids. A simulation study shows that our integrated model accurately recovers the latent counts and prevalence. We apply our model to county-level surveillance data on opioid overdose deaths and treatment admissions from the state of Ohio.

Speaker Bio:  Dr. Staci Hepler is an Associate Professor of Statistics at Wake Forest University in Winston-Salem, North Carolina. She joined the Department of Mathematics and Statistics at WFU in 2015 after completing her PhD in Statistics at The Ohio State University and BS in Integrated Mathematics from Shawnee State University.  Her research interests are in spatio-temporal statistics and Bayesian modeling, with applications to epidemiology and the environmental and ecological sciences. Her current work developing spatio-temporal models to quantify the opioid epidemic in Ohio is supported by the NIH.