Expanding Stanford-CIDE COSMO Modeling Framework and Methodologies for COVID-19 Epidemic Modeling across Diverse Geographies and Populations

Abstract

As COVID-19 transmission leads to its spread throughout the world’s diverse populations, it is critical to efficiently model and forecast its future spread between and within these populations. Doing so supports timely and optimal resource planning and decisions between potentially appropriate and effective interventions. Efficiency in modeling means that we must not invent new models de novo for each population but rather build a set of generally applicable common methodologies and a flexible and scalable framework for model calibration, forecasting, and application to decision analyses and other purposes. Such methodologies and frameworks can then be quickly adapted and applied for particular populations. The goal of this project is to extend, expand, and accelerate the current SC-COSMO framework and methods and to implement these improvements.