Dissertation
Mathematical Modeling, Analysis and Simulation of COVID-19 Dynamics
Washington State University
Doctor of Philosophy (PhD), Washington State University
2023
DOI:
https://doi.org/10.7273/000006340
Abstract
COVID-19 is an infectious disease caused by the SAR-COV-2 virus. Globally, as of 21 February 2023, there have been 757,264,511 confirmed cases of COVID-19, including 6,850,594 deaths, reported to the World Health Organization (WHO). \cite{WHO} The disease dynamics have evolved considerably since the initial outbreak in Wuhan, China with multiple variants, diverse public health measures and shifting public perception. Various public health measures have been implemented in order to slow the spread of including; social distancing, masking and several vaccines have been developed and granted emergency use authorization to help quell the spread of COVID-19. \cite{vaxreview}
Since the onset of the coronavirus pandemic, researchers have been formulating mathematical models to gain insight into the complex dynamics of disease.
In this talk, a model is proposed to study Coronavirus Disease 2019 (COVID-19) with the effect of vaccination with waning immunity. We also consider how hospitalization and COVID-19 specific deaths effect the disease dynamics. Our deterministic model is formulated by a system of ordinary differential equations (ODEs) that is built upon the classical SEIR framework. The local and global dynamics of the disease are analyzed by using the deterministic model with a time dependent vaccination parameter, and the result indicates that the basic reproduction number $\mathcal{R}_0$ serves as a valid disease threshold. Globally the disease dies out if $\mathcal{R}_0 <1$ and locally the disease persists if $\mathcal{R}_0 >1$. The time dependent vaccination parameter was modeled after the historical vaccination trends. Our results indicate that both the exposed and infected classes as well as vaccination play an important role in shaping the epidemic dynamics of COVID-19.}
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Details
- Title
- Mathematical Modeling, Analysis and Simulation of COVID-19 Dynamics
- Creators
- Allison Beth Fisher
- Contributors
- Xueying Wang (Advisor)
- Awarding Institution
- Washington State University
- Academic Unit
- Department of Mathematics and Statistics
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Publisher
- Washington State University
- Number of pages
- 113
- Identifiers
- 99901087336301842
- Language
- English
- Resource Type
- Dissertation