Modeling COVID-19 Spread Using an Agent-Based Network

• Main Author: Hung, Stephen YH
• Format: Others
• Published: DigitalCommons@CalPoly 2021
• Subjects: Covid-19; Agent-Based Model; SARS-CoV-2; Epidemic Model; Simulation; Numerical Analysis and Scientific Computing
• Online Access: https://digitalcommons.calpoly.edu/theses/2356; https://digitalcommons.calpoly.edu/cgi/viewcontent.cgi?article=3874&context=theses

Beginning in 2019 and quickly spreading internationally, the Coronavirus disease Covid-19 became the first pandemic that many people have witnessed firsthand along with the severe disruption to their daily lives. A key field of research for Covid-19 that is studied by epidemiologists, biologists, and computer scientists alike is modeling the spread of Covid-19 in order to better predict future outbreaks of the pandemic and evaluate potential strategies to reduce infections, hospitalizations, and deaths. This thesis proposes a method of modeling Covid-19 spread and interventions for local environments based on different levels of perspective. The goal for this thesis is to be able to present a model of Covid-19 in terms of surrounding areas in San Luis Obispo including the unique mobility dynamic currently held in the global pandemic. Furthermore, we use our model to explore different methods of ensuring a low infection rate such as isolation methods and mobility restrictions.