Simulation of the Spread of COVID-19 at Virginia Tech

Abstract

The IISE community has been offering health-policy insights during the COVID-19 pandemic to keep universities safe for students and employees, and this paper is an example of such ongoing efforts. I developed a generic simulation model of the spread of COVID-19 in universities, which is calibrated for and used at Virginia Tech since April 2020. The model structure follows conventional SEIR-like structures with four major adjustments: 1) it includes the process of diagnosis and test coverage, 2) it represents a university setting in a college town, 3) it considers the weather impact, and 4) it includes behavioral mechanisms to represent students' and employees’ response to growing (or declining) cases. Different sources of quantitative and qualitative data are used in this analysis. The model has provided policy insights at different stages for the university administration including supports for mandating vaccination prior to Fall 2021, as well as guidelines for mask use, testing, and remote versus in-person operations. In this paper, I provide a brief overview of the model and its policy suggestions for the Fall 2021 semester. Then a post-analysis reflection is offered. Finally, we discuss the contributions that the IISE community can make (and is making) to improve COVID-19 related health outcomes.