About

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.

Team

PRIME was written and developed by Cosmin Safta, Jaideep Ray, Patrick Blonigan, and Kamaljit Chowdhary. We would like to acknowledge helpful suggestions made by several colleagues: Erin Acquesta, Thomas Catanach, Bert Debusschere, Sean DeRosa, Pat Finley, Edgar Galvan, Gianluca Geraci, John D. Jakeman, Mohammad Khalil, Khachik Sargsyan, and Teresa Portone.

Acknowledgments

Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525. This work was funded in part by the Laboratory Directed Research & Development (LDRD) program at Sandia National Laboratories and by the US Department of Energy (DOE) Office of Science through the National Virtual Biotechnology Laboratory, a consortium of national laboratories (Argonne, Los Alamos, Oak Ridge, and Sandia) focused on responding to COVID-19, with funding provided by the Coronavirus CARES Act. The views expressed in the article do not necessarily represent the views of the U.S. Department of Energy or the United States Government.

While every effort has been made to produce valid data, by using this data, User acknowledges that neither the Government nor operating contractors of the above national laboratories makes any warranty, express or implied, of either the accuracy or completeness of this information or assumes any liability or responsibility for the use of this information. Additionally, this information is provided solely for research purposes and is not provided for purposes of offering medical advice. Accordingly, the U.S. Government and operating contractors of the above national laboratories are not to be liable to any user for any loss or damage, whether in contract, tort (including negligence), breach of statutory duty, or otherwise, even if foreseeable, arising under or in connection with use of or reliance on the content generated by this software library.

Requirements

The following python packages are required for PRIME, in addition to other default python packages.

• dateutil, h5py, matplotlib, numpy, scipy

We have tested PRIME with python versions 3.6-3.8.