This article focuses on a local scale, which is the UConn main campus. It is important because college campuses are places with high dense populations and easily get infected. From a student’s perspective, building spatial models of campus areas are necessary and help us create a safe community. This study article focuses on building a mathematical model, the Susceptible-Infected-Recovered (SIR) model, and estimates the infectious rate and recovery rate at the University of Connecticut (UConn) Storrs. The model generates the number of cases from August 16, when students who live on campus check-in, to September 7. After finding out the parameters using SIR, we use Agent-Based Modeling (ABM) to simulate different cases to predict and evaluate the risks of different places on campus. 
 
UConn, located in Storrs, has approximately 5,000 students living on campus. Such a population would increase the chances of interaction between students in public places such as academic buildings, dining halls, grocery stores, residential halls, and apartments. Before the semester began, UConn had already announced reopening policies. Most of the classes are moving online or distance learning to prevent the spreading of disease. In-person classes require students wearing a mask and maintaining at least six feet of physical distancing from others. Dining halls are switching to take-out and limited dining models. However, for those students who live in residential halls, even though UConn policy requires one person per dorm room, they are still sharing bathrooms. For those who live in apartments or off-campus, students have approximately one to four roommates, which increases the chance of infection.