Degree Name
Master of Science
Graduate Program
Mathematics
Advisor
Xu, Dashun.
Abstract
This study presents a mathematical model developed to better understand the transmission dynamics of COVID-19 and evaluate the effectiveness of different public health strategies. The model, called SEQIRD, includes of the disease such as exposure, quarantine, infection, recovery, and death. Using real case and death data from Cook County, Illinois, the model closely fits observed trends and captures both pre and post-lockdown dynamics with high accuracy.
Our results show that early intervention significantly reduces total infections, with lockdown imposed even a few days earlier preventing thousands of cases. Through sensitivity analysis, we also identify that parameters such as transmission rate, quarantine effectiveness, and isolation compliance have the largest impact on both epidemic size and basic reproduction number, leading to better disease control results.
Overall, this study offers a new perspective on epidemic modeling by introducing a regionally adaptive control strategy. The findings provide practical guidance for public health officials and policymakers, showing that timely, targeted, and region-specific actions can control disease spread more effectively while minimizing the economic disruption caused by state-wide lockdown.