The goal of this project is to develop interventions for the growing opioid crisis. To do this, the team will build a method to probabilistically fuse granular synthetic household data with publicly available data related to opioid use to predict where opioid hotspots are likely to occur, and why. The predicted hotspots data will then be fused to an agent-based model to simulate potential opioid interventions and determine which ones are likely to work. The partner for this project is a multi-industry nonprofit research institute. MIDS students interested in this project should be interested in, or willing to learn, probabilistic linking and geospatial analysis.