Prediction and Analysis of COVID-19 Cases using Regression Models: A Descriptive Case Study of India

Abstract

The Coronavirus(SARS-CoV-2) is a respiratory illness that emerged in Wuhan, China, on December31, 2019, according to reports by the World Health Organization (WHO). Hospitalrecords in India indicate that COVID-19 hospitalizations in the second wave ofCOVID-19 more than doubled those in the first wave. Limited studies have beenconducted to establish the extent to which the second wave of COVID-19increased the infection status and determine the effectiveness of theintervention strategies employed by the Indian government. This study employedregression models to establish the extent to which government interventions helpedreduce the prevalence of COVID-19 in India, focusing specifically on theKanyakumari, Tirunelveli, Thoothukudi, and Tenkasi districts. The researcherrelied on daily Ministry of Health reports on COVID-19 and generated data forfurther analysis using Statistical Package for Social Sciences (SPSS) software.Findings from the regression analysis show an abnormal rise in the number ofCOVID-19 cases as well as in the number of deaths. However, governmentinterventions such as stay-at-home orders, social distancing, vaccination, andprohibition of social gatherings, among others, helped to significantly reducethe number of COVID-19 cases and deaths in the country. This study thusrecommends that the healthcare sector in India should create long-term interventionsto improve safety and well-being during emergencies.