BU-COVID Modeling

Insight on the Relative Impact of Proposed Interventions for a Large University in an Urban Environment

Katia Bulekova¹, Brian Gregor¹, Eric D. Kolaczyk^2,3, Wenrui Li³, Laura White⁴

¹ Research Computing Services, IS&T, Boston University
² Hariri Institute for Computing, Director, Boston University
³ Department of Mathematics & Statistics, Boston University
⁴ Department of Biostatistics, Boston University

Overview

As with most institutions of higher learning world-wide, Boston University's goal of reopening at some appropriate level in the Fall of 2020 is impacted by many factors. Throughout the early summer of 2020, we conducted a detailed modeling exercise to provide insight into the expected relative efficacy of potential interventions taken around a Fall 2020 BU re-opening. Our approach was to do so in a manner informed as much as reasonably possible by BU data, with a focus primarily on the dynamics around (i) classroom instruction, and (ii) residential housing. In turn, we are making available our software and model parameters, to facilitate other institutions conducting similar analyses.

Obtaining the code

To check out this repository use:

git clone https://github.com/bu-rcs/BU-COVID.git