Date of Award
8-2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Industrial Engineering
Committee Chair/Advisor
Dr. Mary E. Kurz
Committee Member
Dr. Thomas C. Sharkey
Committee Member
Dr. Bryan Lee Miller
Committee Member
Dr. Kevin M. Taaffe
Abstract
The opioid overdose crisis in the United States has led to thousands of lost lives and thousands more people struggling with opioid dependence. Disease modeling allows researchers to examine the course that the disease may take and to investigate policies to determine the effects they may have. Disease models can be used to model non-communicable diseases and have been used to study opioid use disorder. Many types of disease models exist with their own inherent benefits and drawbacks.
In this dissertation, we provide a scoping review of the disease models that have been used to study the opioid overdose epidemic. The scoping review identified 85 articles that developed at least one disease model of the opioid overdose epidemic. The review showed that most disease models are compartmental models (78), and a majority of the models only modeled heroin (49). Fifty-seven were more theoretical and only forty-four used data to inform their modeling. There were three major gaps identified during the scoping review. Most models used country-wide data or no data, only considered heroin use, and were primarily one model type.
Based on the gaps identified in the scoping review, we developed an agent-based model (ABM) of the opioid overdose epidemic. The model addresses gaps in previous research by including using multiple types of opioids, having a criminal justice system influence, modeling different opioid potencies, and including individual characteristics. The ABM has two agent types: human agents, who can misuse opioids, and opioid agents, who supply opioids. The model was run over a five-year time frame and was calibrated to historical data. The agent-based model produced results that are similar to historical averages in overdoses and overdose deaths as well as people who use opioids.
We used the agent-based model to test possible interventions and supply changes. Increasing amounts of fentanyl in drugs has led to higher overdoses and overdose deaths. We chose to model an environment with increasing fentanyl presence, including in other opioids. Due to the increased fentanyl presence, we modeled increased distribution of naloxone, an opioid overdose reversal drug. Distributing naloxone allows bystanders to reverse overdoses, reducing the fatality rate. Results from the model show that the increased proliferation of fentanyl increased overdose deaths while increased naloxone distribution reduced overdose deaths. When both scenarios were simulated, high levels of naloxone mitigated many of the overdose deaths caused by the higher levels of fentanyl.
Recommended Citation
Spence, Chelsea, "Opioid Overdose Epidemic Modeling" (2024). All Dissertations. 3678.
https://open.clemson.edu/all_dissertations/3678