Study on Indian COVID-19 Severity Grades and Vaccine Supply Strategy

In April 2021, amidst the resurgence of the COVID-19 pandemic in India, the dire shortage of vaccines escalated the urgency of effective distribution strategies. This study aims to optimize vaccine supply strategies by leveraging data analytics techniques. Employing RStudio, the research centers on India's first-level administrative regions, employing cluster analysis to categorize regions based on epidemic similarities. Initially, pertinent COVID-19 data and geographical coordinates of administrative regions were gathered for comprehensive analysis and visualization. Descriptive statistics unveiled key insights, aiding in data standardization to ensure equitable clustering. Subsequently, employing statistical metrics, the optimal number of clusters was determined, and hierarchical clustering was employed to generate cluster profiles, visually represented through pedigree diagrams and geographic mappings. Building upon these classifications, severity levels were assigned to regions based on recent case diagnoses, facilitating the formulation of tailored vaccine distribution strategies to mitigate the vaccine shortage effectively. The efficacy of the clustering methodology was evaluated, demonstrating its potential applicability in the nuanced context of India's COVID-19 vaccination campaign, while also laying the groundwork for future research endeavors. By identifying spatial clusters of COVID-19 cases, this study aims to furnish policymakers with actionable insights, enabling them to prioritize interventions in regions most in need. Through its pragmatic approach, this research contributes viable strategies to inform and bolster India's epidemic containment efforts.