PRIME - A Software Toolkit for the Characterization of Partially Observed Epidemics in a Bayesian Framework

PRIME is a modeling framework designed for the “real-time’” characterization and forecasting of partially observed epidemics. Characterization is the estimation of infection spread parameters using daily counts of symptomatic patients. The method is designed to help guide medical resource allocation in the early epoch of the outbreak. The estimation problem is posed as one of Bayesian inference and solved using a Markov Chain Monte Carlo technique. The framework can accommodate multiple epidemic waves and can help identify different disease dynamics at the regional, state, and country levels. We include examples using publicly available COVID-19 data.. Authors: Safta, Cosmin [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0000000172197736); Ray, Jaideep [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0009000099087035); Bridgman, Wyatt [C3 AI, Redwood City, AI (United States)]. DOE Contract: NA0003525. Subjects: 97 MATHEMATICS AND COMPUTING