Mathematical Modeling and Computing to Study the Influence of Quarantine Levels and Common Mitigation Strategies on the Spread of COVID-19 on a Higher Education Campus

Abstract

In this work, we develop a mathematical model to study the COVID-19 dynamics on a higher education campus. The proposed model builds on successful compartmental models that describe the dynamics of the spread of disease between multiple student sub-populations within a closed environment. The model assumes no vaccinations and includes three different levels of quarantine adherence to represent student behavior with the common mitigation strategies of face mask usage and random testing. A detailed analysis of the model including boundedness and positivity of the solutions along with a derivation of the basic reproduction number for the model is presented. Additionally, we also create an interactive graphical user interface through a dashboard for public use.