Prevalence estimates for opioid use disorder (OUD) are essential for guiding investments in prevention and treatment. Previous estimates have been produced using modeling approaches including capture-recapture (CRC). Empirical evaluations of CRC are needed to assess population size impacts of methodological practices utilized. We linked administrative data sources including New York State (NYS) adults with OUD by indication between January 1-December 31, 2020 and applied Bayesian CRC methods to evaluate how methodological practices impact OUD prevalence: (1) using sensitive versus specific case definition characteristics to identify OUD, (2) including versus excluding inferred referrals from emergency medical services to healthcare settings, and (3) including versus excluding overdose mortality as a source list. We estimated OUD prevalence overall and by demographic characteristics and treatment coverage with medications for OUD (MOUD). Across methodological scenarios, OUD prevalence estimates ranged from 4.6%-9.9%. The largest estimate resulted from a model in which the more sensitive OUD case definition was applied, while the smallest resulted from a model using the more specific case definition. An estimated 4.2% of NYS adults had OUD in 2020, with 20% receiving MOUD. Findings demonstrate that CRC methodological decisions can meaningfully influence OUD prevalence estimates, with recommended methodological practices provided.
A comparative analysis of methodological practices used in capture-recapture population size estimation: Opioid use disorder prevalence in New York State, 2020
American Journal of Epidemiology [Epub 2026 Jul 10]. doi: 10.1093/aje/kwag161.