Leveraging spatiotemporal Bayesian analysis to unravel polysubstance use and overdose risk: Opportunities and challenges

Abstract

In the current wave of the opioid epidemic, the prevalence of polysubstance use continues to complicate drug-related deaths. Most studies to date use non-spatial statistical approaches to examine the association between polysubstance use and overdose risk, without considering the spatial distribution of these latent sub-patterns of use. This paper describes the utility and potential impact of using disease mapping and Bayesian spatiotemporal approaches for analyzing and monitoring polysubstance use and overdose risk to better respond to the ongoing opioid epidemic. We discuss the application of Bayesian spatiotemporal approaches in analyzing polysubstance use among people who use drugs. Bayesian spatiotemporal analyses offer a salient approach to detecting localized distributions of overdose events and tailor local interventions to community needs in order to reduce polysubstance use and related adverse health among people who use drugs. This can help improve precision and efficacy response in reducing polysubstance use adverse outcomes and optimize resource allocation.

Keywords: Disease mapping; Geospatial health; Overdose; Polysubstance use; Public health; Spatiotemporal analysis.