Modeling for COVID-19 Infections and Deaths in Tamil Nadu, India, Using Panel Regression Model

Abstract

The impacts of the coronavirus disease 2019 (COVID-19) pandemic have been extremely severe, with both economic and health crises experienced worldwide. The incidence of novel COVID-19 infections dramatically increased due to the absence of antiviral medications and vaccines, resulting in enormous economic losses, panic, and many deaths. Based on the panel regression model, this study examined the trends and correlations in the number of COVID-19-related deaths and the number of COVID-19-infected cases in all 37 regions of the Tamil Nadu state in India in August 2020. The fixed effects model had the most excellent R² value of 78% and exhibited significant results. The slope coefficient was also highly effective, showing a considerable variation in the relationship between new COVID-19 cases and deaths. Additionally, for every unit increase in COVID-19-infected instances, the death rate increased by 0.02%. The main issue with this model is that it did not differentiate between the various districts or inform us whether the overall COVID-19 mortality response to the explanatory variable over time was consistent across all neighborhoods.