Using Mathematical Models to Investigate how Socioeconomic Factors Influence Opioid and Heroin Addiction by Veronica Berger ’22, Mathematics Senior Thesis Defense, Monday, May 16, 1 – 1:40 pm, North Science Building 113, Wachenheim.
Abstract: Disease modeling has been instrumental in understanding the development of diseases such as HIV, COVID-19, and hundreds of others. The most common form of these models are compartmental differential equations that are based on the “Susceptible (S) – Infected (I) – Recovered (R)” paradigm. Here, we adapt disease modeling to consider questions related to opioid and heroin addiction. Opioid and Heroin addiction have caused an epidemic in the U.S. since the 1990s with almost 400,000 lives lost to overdose between 1999 and 2017. This addiction model focuses on the effect of insurance coverage in the addiction, treatment, and recovery process. Using the model, different situations can be analyzed: what is opioid and heroin addiction like in low-income communities (likely to have a large uninsured population), what is addiction like in high-income communities (more likely to have a large insured population with more expendable income). The model urges more expansive insurance coverage by showing the risk of addiction in low-income communities.