Author

Xiaorui Bao

Date of Award

2023

First Advisor

Kenneth Knox

Second Advisor

Sarah Snyder

Abstract

This thesis is an adaptation and extension of the topic of my final project in my ODE (Ordinary Differential Equations) course. The ODE course took place during a period when COVID-19 was at its peak two years ago. This motivated me to conduct this research. Now, two years later, I am revisiting the study of modeling and the novel coronavirus. In this thesis, I present an analysis of the COVID-19 pandemic using a differential equation model known as the SIR (Susceptible-Infectious-Recovered) model. The introduction provides an overview of the topic, emphasizing the significance of mathematical modeling in understanding and managing infectious diseases. The development of the SIR model is discussed, including the symbolic description, model assumptions, and its establishment. Subsequent sections focus on improving the model and extending its application to both within and outside the Hubei Province, the epicenter of the COVID-19 outbreak. Within the Hubei Province, the model assumptions are outlined, and the model is established to simulate the spread of the virus. The determination of parameters crucial for the model's accuracy is also discussed. Moving beyond Hubei, the study explores the application of the SIR model in other regions, considering variations in assumptions and parameter determination. Furthermore, this thesis addresses the role of mathematicians during the COVID-19 pandemic. It highlights the contribution of math professionals in developing and refining models, analyzing data, and providing valuable insights to policymakers and healthcare authorities.

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