Document Type

Pre-Print

Publication Date

2-24-2020

Subjects

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

Abstract

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.

Methods
: 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.

Results
: 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.

Conclusion
: 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.

Description

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 It has not been peer-reviewed.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

https://archives.pdx.edu/ds/psu/32340

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

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