ABSTRACT
World is facing impact of COVID pandemic;every industry is facing corollaries to a great extent. With increase in number of COVID cases, it is necessary to control the spread of virus and wipe it out in the best possible manner. COVID-19, which have its rapid spread across the world, is a dangerous episode which entire community is cladding on. Proper treatment and efficient vaccine distribution are the major glitches of medical industry during this untoward outbreak. Priority in distribution of vaccine is extremely vital, to handle availability of vaccines. Our main objective is to develop methodologies with competing process which implements unsupervised k-means clustering and supervised naïve Bayes, decision tree and gradient boost classification algorithms to find the priority of individuals for distributing vaccines. Efficient pathway of distribution is implemented in layered manner based on individual’s priority, assessed in par with impact level of disease on individuals in the community. Priority for vaccine distribution is finalized with classification algorithm with the highest accuracy. It helps to distribute the available vaccines optimally among the population, and it plays major role in reducing the impact of coronavirus on individuals and society. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.