Author ORCID Identifier

0000-0001-7888-3809

Date of Award

Spring 5-14-2021

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Public Health

First Advisor

Dr. Heather Bradley

Second Advisor

Dr. Gerardo Chowell

Third Advisor

Dr. Alana Vivolo-Kantor

Abstract

Unintentional drug overdose is a persistent and pervasive public health threat in the U.S. The current epidemic is driven mainly by opioids, especially synthetic opioids like fentanyl. However, the landscape of drug use is constantly shifting, with novel substances emerging and old threats, such as cocaine and psychostimulants, re-emerging. Additionally, overdose is preventable through harm reduction, supply interruption, addiction treatment, and other means of reducing drug use or making drug use safer. Public health requires tools to monitor these changes and even better, to predict what will happen next, in order to prevent overdose and other adverse effects of drug use. While current surveillance for overdose has evolved rapidly in a short time, gaps remain, mainly in the areas of timeliness and specificity.

The studies in this dissertation attempt to fill these surveillance gaps. The first study introduces methods for analyzing a novel laboratory drug testing data source. This data source includes results from a large commercial clinical laboratory system with testing sites throughout the country. This system performs drug tests for a variety of reasons, including therapeutic and pain medication monitoring, addiction treatment, workplace testing, and prenatal and neonatal testing. Drug category positivity stratified by age, sex, and reason for order from the first year of available data are presented, along with a discussion of the best uses and limitations. The second study uses the same data set for a spatial analysis of counties in the U.S. Positivity rates for four drug categories are presented for the U.S. and selected states; hotspots of positivity are also identified. And finally, the third study explores the utility for predicting overdose mortality of a forecasting model that is typically used for short-term forecasts for infectious disease outbreaks. Forecasting future overdose activity is essential for public health to outmaneuver an epidemic that does not seem to be slowing down.

The findings from these three studies will fill gaps for surveillance efforts by incorporating a new data source and new analyses that can be used to provide public health professionals with tools needed for timely situational awareness. This will ideally lead to more effective implementation of evidence-based interventions to prevent overdose.

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