Invited commentary: Motivating better methods—and better data collection—for measuring prevalence of drug misuse

Abstract The United States continues to suffer a drug overdose crisis that has resulted in over 100 000 deaths annually since 2021. Despite decades of attention, estimates of the prevalence of drug use at the spatiotemporal resolutions necessary for resource allocation and intervention evaluation are lacking. Current approaches for measuring the prevalence of drug use, such as population surveys, capture–recapture, and multiplier methods, have significant limitations. In a recent article, Santaella-Tenorio et al (Am J Epidemiol. 2024;193(7):959-967) used a novel joint bayesian spatiotemporal modeling approach to estimate the county-level prevalence of opioid misuse in New York State from 2007 to 2018 and identify significant intrastate variation. By leveraging 5 data sources and simultaneously modeling different opioid-related outcomes—such as numbers of deaths, emergency department visits, and treatment visits—they obtained policy-relevant insights into the prevalence of opioid misuse and opioid-related outcomes at high spatiotemporal resolutions. The study provides future researchers with a sophisticated modeling approach that will allow them to incorporate multiple data sources in a rigorous statistical framework. The limitations of the study reflect the constraints of the broader field and underscore the importance of enhancing current surveillance with better, newer, and more timely data that are both standardized and easily accessible to inform public health policies and interventions. This article is part of a Special Collection on Mental Health.