Dissertation
Mathematical Modeling of SARS-COV-2 Infection Spread in Enclosed Spaces With Ventilation Using Numerical and Agent Techniques
Washington State University
Doctor of Philosophy (PhD), Washington State University
2023
DOI:
https://doi.org/10.7273/000005235
Abstract
This dissertation will delve into the two mathematical models that my collaborators and I have created to better understand the nuances of SARS-CoV-2 in circumstances involving ventilation. The first model takes into account the Wells-Riley model which deals with quantums of infection. We combined this approach with a multi-age SEIR model to understand why the world saw such devastating infection rates in places where specifically the elderly congregate. We applied this model to a hypothetical nursing home scenario using interpersonal contact data and compared that against different ventilation scenarios, and found that even with incredible filtration systems it was unlikely SARS-CoV-2 would have been stopped from spreading to the elderly. In a similar vein, we then moved on to creating a stochastic agent model where we would be able to understand how spacial positioning would play a role in the likelihood of illness for those around a main infector.
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Details
- Title
- Mathematical Modeling of SARS-COV-2 Infection Spread in Enclosed Spaces With Ventilation Using Numerical and Agent Techniques
- Creators
- Matthew Gaddis
- Contributors
- Valipuram S Manoranjan (Advisor)Xueying Wang (Committee Member)Sergey Lapin (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- Mathematics and Statistics, Department of
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Publisher
- Washington State University
- Number of pages
- 105
- Identifiers
- 99901019635301842
- Language
- English
- Resource Type
- Dissertation