Author ORCID Identifier

https://orcid.org/0000-0001-7595-9791

Date of Award

5-4-2022

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Yingshu Li

Second Advisor

Zhipeng Cai

Third Advisor

Yanqing Zhang

Abstract

Vaccination is the preventative measure that effectively decelerates the virus proliferation in a community. A successful response strategy toward pandemics can be obtained through selecting the optimal vaccine distribution route and minimizing the casualties by lowering the death rate and infection rate. In this thesis paper, we propose the Epidemic Vulnerability Index (EVI) that quantifies the potential risk of the subject via analyzing the COVID-19 patient dataset that correlates with mortality and social network analysis that affects the infection rate. We propagate the virus and vaccination in an Agent-based model based on real-world statistics of physical connections and features to 300,000 agents with nine vaccination criteria, including EVI. Vaccination through descending order of EVI has shown the best performance with the numerical outcome of 5.0% lower infection cases, 9.4% lower death cases, and 3.5% lower death rates than the average of other vaccination dissemination criteria.

DOI

https://doi.org/10.57709/28834613

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