A Gaussian process and gradient boosting emulation framework is used to search millions of policy combinations for a COVID-19 agent-based model, identifying mixed low-intensity strategies that would have reduced St. Louis Omicron infections and geographic disparity.
Guidance for Antigen Testing for SARS- CoV-2 for Healthcare Providers Testing Individuals in the Community, 2020
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Start from the End: A Framework for Computational Policy Exploration to Inform Effective and Geospatially Consistent Interventions applied to COVID-19 in St. Louis
A Gaussian process and gradient boosting emulation framework is used to search millions of policy combinations for a COVID-19 agent-based model, identifying mixed low-intensity strategies that would have reduced St. Louis Omicron infections and geographic disparity.