Modeling School Reopening Options in Response to COVID-19

Abstract

School administrators have the daunting challenge of rolling out school reopening policies and safety standards. While it is important to have children in school to maximize learning, it is critical to ensure that it is done in a manner which prioritizes the safety of staff and students on campus. This research explores models that can be used to examine the spread of COVID-19, and then applies them to evaluate school reopening policies within the United States. A variety of factors are accounted for, including the student population, the rate at which students are infected, the rate at which students are quarantined, and the proportion of students that are susceptible to COVID-19. We primarily utilize Euler’s method and nondimensionalization of the differential equations for each model. Our graphical results are displayed using Excel. We show that multiple variables such as rate of infection and recovery can be written solely as a function of one parameter: R0. We first analyze the SIR model and then introduce the new scenario of quarantining students to derive the SIQR model. Our findings show that reducing and maintaining R0 below 1 is the key to reopening schools and we outline practices to help achieve this outcome.