Epidemic Vulnerability Index for Effective Vaccine Distribution Against Pandemic


연구 분야: Strategies



학회: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Volume 20, Issue 6


초록

COVID-19 vaccine distribution route directly impacts the community's mortality and infection rate. Therefore, optimal vaccination dissemination would appreciably lower the death and infection rates. This paper proposes the Epidemic Vulnerability Index (EVI) that quantitatively evaluates the subject's potential risk. Our primary aim for the suggested index is to diminish both infection rate and death rate efficiently. EVI was accordingly designed with clinical factors determining the mortality and social factors incorporating the infection rate. Through statistical COVID-19 patient dataset analysis and social network analysis with an agent-based model that is analogous to a real-world system, we define and experimentally validate the capability of EVI. Our experiments consist of nine vaccination distribution scenarios, including existing indexes which estimate the risk and stochastically proliferate the contagion and vaccine in a 300,000 agent-based graph network. We compared the outcome and variation of the three metrics in the experiments: infection case, death case, and death rate. Through this assessment, vaccination by the descending order of EVI has shown to have a significant outcome with an average of 5.0% lower infection cases, 9.4% lower death cases, and 3.5% lower death rate than other vaccine distribution routes.


Author Profile
Hunmin Lee

Department of Computer Science and Engineering University of Minnesota Twin Cities MN USA

Andorra
Author Profile
Mingon Kang

Department of Computer Science University of Nevada Las Vegas NV USA

United States
Author Profile
Donghyun Kim

Department of Computer Science Georgia State University Atlanta GA Georgia

Gabon

📄 논문 정보

발행 연도 2022년
인용수 0
출판 국가 Gabon, Andorra, United States, Korea
사이트 ACM
좋아요 수 0

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