Date of Award

5-2022

Document Type

Thesis

Degree Name

Master of Science (MS)

College/School

College of Science and Mathematics

Department/Program

Applied Mathematics and Statistics

Thesis Sponsor/Dissertation Chair/Project Chair

Eric Forgoston

Committee Member

Baojun Song

Committee Member

David Trubatch

Abstract

The emergence of the novel coronavirus (SARS-CoV-2) in late 2019 has led to a global pandemic (COVID-19) which continues to cause enormous public health and economic challenges around the world. It is therefore important to improve our understanding of the outbreak and spread of COVID-19 as well as to investigate how one might contain or stop the spread of COVID-19 via different control measures. In this thesis, we consider a COVID-19 model based on an SEIR compartmental model. The model includes susceptible, vaccinated, exposed, pre-symptomatic, symptomatic infectious, asymptomatic infectious, hospitalized, recovered, and deceased compartments, each of which is sub-divided into 17 age groups. Furthermore, we incorporate contact structure which accounts for the number of contacts that individuals experience at school, work, home, and other environments. The model is parameterized based on New Jersey data, and we consider the effect of a hypothetical vaccine of varying efficacy that is introduced at the start of the epidemic outbreak in New Jersey. The results demonstrate how different control measures, including vaccine and lockdown, interact with each other and lead to different epidemic outcomes.

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