Mathematical Modeling of COVID-19 Dynamics on a College Campus: A Story of Differential Equations, Network Theory and Presentations to Campus Leadership
In March 2020 the University of California, Merced (UC Merced), along with all higher educational institutions in the state of California, moved to an on-line only mode of course delivery as a means to decrease the spread of SARS-CoV-2, or COVID-19. In Summer 2020, a Public Health Working group was convened to plan for the Fall 2020 semester. As mathematical biologists, we were tasked to develop mathematical models to evaluate the effectiveness of proposed disease mitigation strategies in containing COVID-19 at UC Merced. In this talk, we discuss both the results of our modeling efforts as well as our perspective on how mathematicians can effectively engage with campus leadership in the decision-making process. Finally, we report on our on-going efforts to provide UC Merced with data for Spring 2021 planning.
We will present the two mathematical models we used to evaluate Fall 2020 re-opening strategies: a system of ordinary differential equations and an agent based model. Perhaps not surprisingly, our models demonstrated that even when the campus undertook strong disease mitigation measures (limiting the size of in-person courses, testing of symptomatic & asymptomatic individuals and mandatory mask-use) COVID-19 would continue to enter the UC Merced campus population through less restrictive contacts with the surrounding community. As such, the campus would have to be prepared for a steady stream of active cases all semester. In July 2020, UC Merced made the decision to hold all classes remotely and our models were used to determine a “safe number” of students to allow in on-campus housing.
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