Multi-Parameter Estimation of Prevalence (MPEP): A Bayesian modelling approach to estimate the prevalence of opioid dependence

TL;DR

This paper introduces MPEP, a Bayesian approach using administrative data to estimate the prevalence of hidden populations like opioid dependence, improving accuracy and consistency checks over traditional methods.

Contribution

The paper presents the MPEP Bayesian model, enhancing prevalence estimation by leveraging linked administrative data and addressing limitations of capture-recapture methods.

Findings

MPEP provides consistent prevalence estimates across multiple data sources.

The approach improves computational efficiency with an implementation in STAN.

Case study estimates opioid dependence prevalence in Scotland from 2014 to 2022.

Abstract

Estimating the number of the number of people from hidden and/or marginalised populations - such as people dependent on opioids or cocaine - is important to guide policy decisions and provision of harm reduction services. Methods such as capture-recapture are widely used, but rely on assumptions that are often violated and not feasible in specific applications. We describe a Bayesian modelling approach called Multi-Parameter Estimation of Prevalence (MPEP). The MPEP approach leverages routinely collected administrative data, starting from a large baseline cohort of individuals from the population of interest and linked events, to estimate the full size of the target population. When multiple event types are included, the approach enables checking of the consistency of evidence about prevalence from different event types. Additional evidence can be incorporated where inconsistencies are identified. In this article, we summarize the general framework of MPEP, with focus on the most recent version, with improved computational efficiency (implemented in STAN). We also explore several extensions to the model that help us understand the sensitivity of the results to modelling assumptions or identify potential sources of bias. We demonstrate the MPEP approach through a case study estimating the prevalence of opioid dependence in Scotland each year from 2014 to 2022.