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 to measure prevalence of drug use, such as population surveys, capture-recapture, and multiplier methods, have significant limitations. Santaella-Tenorio et al. (Am J Epidemiol. XXXX;XXX(XX)XXXX-XXXX)) use a novel joint Bayesian spatiotemporal modeling approach to estimate county-level opioid misuse prevalence in New York state from 2007 to 2018 and identify significant intra-state variation. By leveraging five data sources and simultaneously modeling different opioid-related outcomes - such as deaths, emergency department visits, and treatment visits - they obtain policy-relevant insights into the prevalence of opioid misuse and opioid-related outcomes at high spatiotemporal resolutions. This study provides future researchers with a sophisticated modeling approach that allows them to incorporate multiple data sources in a rigorous statistical framework. The limitations of the study reflect the constraints of the broader field and underscores the importance of enhancing current surveillance with better, newer, and more timely data that is both standardized and easily accessible to inform public health policies and interventions.