PROJECT SUMMARY Between April 2021 and March 2022, the U.S. endured over 100,000 drug overdose deaths. As the opioid epidemic expands, the epidemiology of overdose is changing. Nationally, the rate of overdose in Black and Latinx people is growing more than five times faster than it is among white people. Similarly, between 1999- 2015, the prescription opioid overdose rate among women increased at more than twice the rate for men. While differences in opioid supply could explain some racial and gender disparities, the ways that we implement opioid treatment could also drive them. It is therefore essential that we investigate how implementation of policy and interventions to address the opioid crisis impacts health equity. The Researching Effective Strategies to Prevent Opioid Death (RESPOND) is simulation model OUD and OUD treatment delivery in a state. RESPOND leverages investments in expanded public health data infrastructure to inform model parameters, and it catalyzes new uses of data from NIDA-funded implementation studies. We use RESPOND to investigate the health benefits, costs, and cost-effectiveness of policy choices and health care delivery models to prevent opioid overdose. In the previous funding period, we developed RESPOND and published studies projecting public health and health economic impacts of expanding the availability of medications for opioid use disorder (MOUD) in a variety of settings. We are currently expanding RESPOND to simulate outcomes in Kentucky, Ohio, and New York. We now propose to enhance RESPOND to investigate outcomes among populations of special interest to opioid response: 1) communities of color and 2) women. We will then use the model to investigate health economic and health equity impacts of policies regulating prescribing for medications for OUD and innovative care delivery models for people with OUD. We will perform distributional cost-effectiveness analyses, which is an emerging and innovative method to investigate trade-offs between maximizing population-level benefits and ensuring equitable distribution of costs and benefits. Our specific aims are: Aim 1: To enhance the RESPOND model and calibrate it to race and gender stratified targets in order to focus on populations of interest in the opioid crisis: people of color and women Aim 2: To use RESPOND to perform distributional cost-effectiveness analyses of changing policies regulating MOUD prescribing Aim 3: To employ RESPOND to investigate the clinical, racial equity impact, and economic value of interventions that support people who use drugs along each step of the OUD care cascade. We use RESPOND to generate evidence to guide large-scale implementation of policies and interventions to prevent overdose. In the coming 5-years we will continue to be leaders in the field of OUD simulation modeling and will employ RESPOND as an important tool for justice in the opioid crisis.