Epidemic Vulnerability Index for Effective Vaccine Distribution Against Pandemic

Document Type

Conference Proceeding

Publication Date


Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)


13064 LNBI

First page number:


Last page number:



As COVID-19 vaccines have been distributed worldwide, the number of infection and death cases vary depending on the vaccination route. Therefore, computing optimal measures that will increase the vaccination effect are crucial. In this paper, we propose an Epidemic Vulnerability Index (EVI) that quantitatively evaluates the risk of COVID-19 based on clinical and social statistical feature analysis of the subject. Utilizing EVI, we investigate the optimal vaccine distribution route with a heuristic approach in order to maximize the vaccine distribution effect. Our main criterias of determining vaccination effect were set with mortality and infection rate, thus EVI was designed to effectively minimize those critical factors. We conduct vaccine distribution simulations with nine different scenarios among multiple Agent-Based Models that were constructed with real-world COVID-19 patients’ statistical data. Our result shows that vaccine distribution through EVI has an average of 5.0% lower in infection cases, 9.4% lower result in death cases, and 3.5% lower in death rates than other distribution methods.


Agent based model; Clinical data analysis; COVID-19; Epidemic vulnerability index; Social data analysis


Immunology and Infectious Disease | Immunology of Infectious Disease

UNLV article access

Find in your library