Supplement for Cloud Computing: Opioid Policy Models

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PROJECT SUMMARY/ABSTRACT In our study, Opioid Policy Modeling in North Carolina (5R01DA04799), we developed an agent-based simulation model (ABM) to inform policy makers and health professionals in North Carolina about local and state-wide interventions to reduce opioid overdoses and related deaths. Interventions are identified in the NC Opioid Action Plan and cover the Three Pillars: prevention, connection to care, and harm reduction. Our ABM represents a community (e.g., a county, town) of networked individuals (e.g., patients, physicians, dealers), and simulates how proposed interventions affect individual pathways to opioid misuse and other outcomes (i.e., OD death). The model relies on a synthetic population representing every individual in the United States, which allows information from multiple datasets to be probabilistically connected in one model. Synthetic individuals are positioned in geospatial context that includes the locations of hospitals, other treatment facilities, and service providers. Cloud infrastructure will allow us to speed up realistic simulations and consider more scenario options than are considered on a current “in-house” computational infrastructure. It will enable us to develop a meta- model summarizing a multitude of scenarios. Benefits of cloud computing will affect geospatial calibration, validation, and scenario simulations.