Prioritizing COVID-19 Vaccine Delivery for the Indian Population

Abstract

As India has successfully developed a vaccine to fight against the COVID-19 pandemic, the government has started its immunization program to vaccinate the population. Initially, with the limited availability in vaccines, a prioritized roadmap was required to suggest public health strategies and target priority groups on the basis of population demographics, health survey information, city/region density, cold storage facilities, vaccine availability, and epidemiologic settings. In this paper, a machine learning-based predictive model is presented to help the government make informed decisions/insights around epidemiological and vaccine supply circumstances by predicting India's more critical segments that need to be catered to with vaccine deliveries as quickly as possible. Public data were scraped to create the dataset; exploratory data analysis was performed on the dataset to extract important features on which clustering and ranking algorithms were performed to figure out the importance and urgency of vaccine deliveries in each region.