Empirical calibration of a simulation model of opioid use disorder.

ABSTRACT:

Background

Simulation models of opioid use disorder (OUD) aim at evaluating the impact of different treatment strategies on population-level outcomes. Researching Effective Strategies to Prevent Opioid Death (RESPOND) is a dynamic population, state-transition model that simulates the Massachusetts OUD population synthesizing data from multiple sources. Structural complexity and scarcity of available data for opioid modeling pose a special challenge to model calibration. We propose an empirical calibration approach applicable to complex simulation models in general.

Methods

We implement an empirical approach to calibrate RESPOND to multiple targets: annual fatal opioid-related overdoses, detox admissions, and OUD population sizes. The empirical calibration involves Latin hype

SUBMITTER: Madushani RWMA 

PROVIDER: S-EPMC11949371 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature