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Opioid abuse -- United States -- Simulation, Opioid abuse -- Treatment, System analysis


Background: The U.S. opioid epidemic has caused substantial harm for over 20 years. Policy interventions have had limited impact and sometimes backfired. Experts recommend a systems modeling approach to address the complexities of opioid policymaking.

Objectives: Develop a system dynamics simulation model that reflects the complexities and can anticipate intended and unintended intervention effects.

: The model was developed from literature review and data gathering. Its outputs, starting 1990, were compared against 12 historical time series. Illustrative interventions were simulated for 2020-2030: reducing prescription dosage by 20%, cutting diversion by 30%, increasing addiction treatment from 45% to 65%, and increasing lay naloxone use from 4% to 20%. Sensitivity testing was performed to determine effects of uncertainties. No human subjects were studied.

: The model fits historical data well with error percentage averaging 9% across 201 data points. Interventions to reduce dosage and diversion reduce the number of persons with Opioid Epidemic Dynamic Policy Model 2 opioid use disorder (PWOUD) by 11% and 16%, respectively, but each reduces overdoses by only 1%. Boosting treatment reduces overdoses by 3% but increases PWOUD by 1%. Expanding naloxone reduces overdose deaths by 12% but increases PWOUD by 2% and overdoses by 3%. Combining all four interventions reduces PWOUD by 24%, overdoses by 4%, and deaths by 18%. Uncertainties may affect these numerical results, but policy findings are unchanged.

: No single intervention significantly reduces both PWOUD and overdose deaths, but 43 a combination strategy can do so. Entering the 2020s, only protective measures like naloxone 44 expansion could significantly reduce overdose deaths.


This is an original manuscript / pre-print of an article submitted for publication in American Journal of Drug and Alcohol Abuse (Taylor & Francis). It has not been peer-reviewed. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document.

Persistent Identifier

Ref Guide Opioid2u Feb2020.pdf (614 kB)
Reference Guide for the Opioid Epidemic Simulation Model: An Evidence-Based Tool for What-If Scenario Testing