Title: Using mechanistic models to advance theory in opioid use disorder epidemiology

 

Abstract: Opioid use disorder has been a national health crisis in recent years, with high economic costs and opioid involvement in over 70% of all drug overdose deaths in 2019. Widespread opioid use has its roots in prescription medication – a fact which greatly increases the population’s exposure and mathematically suggests non-contact-based routes of addiction. In this talk, I will describe two recent mathematical models for opioid use disorder and treatment, including dynamics involving heroin and fentanyl in the context of data for the state of Tennessee. I will also show how these models, as well as population models for alcohol use disorder, exhibit fundamentally different dynamics from infectious disease models and therefore require a different approach to analysis. Finally, I will present an agent-based, social-network approach we are working on that complements our population-level modeling and shows promise for teasing out certain micro-level, heterogeneous dynamics related to the social spread of opioid use disorder.