The Opioid County Policy Simulator (the Simulator) is a tool to help policymakers simultaneously evaluate the public health and economic implications of implementing evidence-based policy scenarios in their county of interest. The Simulator shows the impact on opioid overdose deaths and health costs of increasing medication initiation and retention, and naloxone distribution. Medication is differentiated by type: buprenorphine, methadone, and naltrexone. Costs include medication costs, naloxone costs (including distribution), emergency medical services for fatal and non-fatal overdoses; and healthcare utilization costs, stratified by outpatient, inpatient, emergency department, and residential settings. The tool uses a mathematical model to simulate 5-year projections for all US counties. The user selects the county of interest, as well as scenarios to simulate.
To use the simulator, please follow the steps below. Informational bubbles have been added throughout the tool to provide additional relevant information on the specific sections.
Step 1: Select the county you would like to simulate using the state and county dropdown.
- Note: At least one value for each relevant disease burden and cost input will be automatically populated based on relevant survey or trial data. After selecting your county of interest, you can customize any of the relevant pre-populated data to fit your needs.
Step 2: Select the intervention(s) you would like to simulate. The user can alter the MOUD initiation, MOUD retention, and Naloxone levels.
- Note: Currently, up to two scenarios can be added simultaneously to allow for easy direct comparisons.
Step 3: Run the model and generate the results. Once all the relevant input data has been edited, if necessary, the user can run the model and generate results related to the disease burden and cost impact of the intervention(s) simulated.
The Simulator is a tool to help you understand the overall impact of various strategies in reducing the burden of opioid use. It relies on a mathematical model to generate its results. Because results include some simulation noise, users should keep in mind that the results produced by the Simulator to be approximate, rather than exact.
