The opioid crisis in the midst of the COVID-19 pandemic: spatiotemporal analysis of opioid-involved mortality in the context of the COVID-19 pandemic in a major U.S. metropolitan area

Keywords: Spatiotemporal Analysis, Substance Use, COVID-19, Machine Learning
Session Type: Virtual Paper Abstract
Day: Tuesday
Session Start / End Time: 3/1/2022 11:20 AM (Eastern Time (US & Canada)) - 3/1/2022 12:40 PM (Eastern Time (US & Canada))
Room: Virtual 17

Abstract

The global pandemic of SARS-CoV-2 (COVID-19) quickly became the most concerning public health issue in 2020, affecting hundreds of millions of people across the globe. The National Institute of Environmental Health Sciences has stated that nearly half of Americans have reported that their mental health has been negatively impacted by COVID-19 due to stress arising from social isolation, job losses, and lack of access to healthcare among other reasons. In addition to impacting mental health, the COVID-19 pandemic has also been reported to impact individuals with opioid use disorder in the United States. Opioid treatment service deliveries were frequently disrupted during the time of the pandemic. Recent studies have shown that over 30 states reported increased opioid-involved fatalities during the pandemic. This study focused on analyzing opioid-involved mortality in the context of the COVID-19 pandemic in Chicago, IL, from a geospatial perspective. We investigated the spatiotemporal patterns of drug-related deaths for all opioids as well as for heroin, fentanyl, and cocaine that occurred in Chicago during 2020. We compared the spatiotemporal patterns of opioid-involved deaths with patterns for the previous three years (2017-2019) to understand changes in the context of COVID-19. A space-time random forest model was used to analyze the relationships between opioid deaths, COVID-19 deaths and COVID-19 positive cases at ZIP code level, and reveal associations with sociodemographic characteristics as well as mobility behaviors during the pandemic. The results are used to generate a space-time risk map relating to opioid deaths during the COVID-19 pandemic.