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 December 31, 2019, according to reports by the World Health Organization (WHO). Hospital records in India indicate that COVID-19 hospitalizations in the second wave of COVID-19 more than doubled those in the first wave. Limited studies have been conducted to establish the extent to which the second wave of COVID-19 increased the infection status and determine the effectiveness of the intervention strategies employed by the Indian government. This study employed regression models to establish the extent to which government interventions helped reduce the prevalence of COVID-19 in India, focusing specifically on the Kanyakumari, Tirunelveli, Thoothukudi, and Tenkasi districts. The researcher relied on daily Ministry of Health reports on COVID-19 and generated data for further analysis using Statistical Package for Social Sciences (SPSS) software. Findings from the regression analysis show an abnormal rise in the number of COVID-19 cases as well as in the number of deaths. However, government interventions such as stay-at-home orders, social distancing, vaccination, and prohibition of social gatherings, among others, helped to significantly reduce the number of COVID-19 cases and deaths in the country. This study thus recommends that the healthcare sector in India should create long-term interventions to improve safety and well-being during emergencies