Publications / SAND Report

Rapid Response Data Science for COVID-19

Bandlow, Alisa B.; Bauer, Travis L.; Crossno, Patricia J.; Garcia, Rudy J.; Astuto Gribble, Lisa A.; Hernandez, Patricia M.; Martin, Shawn; McClain, Jonathan T.; Patrizi, Laura P.

This report describes the results of a seven day effort to assist subject matter experts address a problem related to COVID-19. In the course of this effort, we analyzed the 29K documents provided as part of the White House's call to action. This involved applying a variety of natural language processing techniques and compression-based analytics in combination with visualization techniques and assessment with subject matter experts to pursue answers to a specific question. In this paper, we will describe the algorithms, the software, the study performed, and availability of the software developed during the effort.