Date of Award

Fall 12-10-2021

Document Type

Honors Project

Degree Name

Bachelor of Science



Department Chair or Program Director

Esunge, Julius

First Advisor

Lee, Jangwoon "Leo"

Major or Concentration



In this research project, we used numerical methods to investigate trends in the susceptible, exposed, infectious, quarantined, recovered, closed cases and insusceptible populations for the COVID-19 pandemic in 2021. We used the SEIQR model containing seven ordinary differential equations, based on the SIR model for epidemics. An analytical solution was derived from a simplified version of the model, created by making various assumptions about the original model. Numerical solutions were generated for the first 100 days of 2021 using algorithms based on Euler's Method, Runge-Kutta Method, and Multistep Methods. Our goal is to show that numerical methods can help us predict trends in the populations we are studying and provide insight for steps that can be taken to reduce the number of infections.