Forecasting the outbreak and spread of COVID-19 in India and Tamilnadu using logistic growth and SIR models

ABSTRACT

The whole world faces an uncommon situation in its history due to the spread of the novel coronavirus (COVID-19). First impacted its existence during December 2019 in Wuhan City, Hubei Province, China. However, the spread of the disease is marginally visible and resulting in an epidemic distribution across capital cities of India. As of June 15, 2020, in India, 368705 are the confirmed cases, and 12280 people have deceased their lives. Collecting the statistics of daily infections, deaths and recovery data and predicting epidemic trends of COVID-19 in India has the most significant importance for developing and measuring the impacts of public intervention strategies. Based on India and Tamil Nadu's initial 105 days of COVID-19 statistics of (one of its states), we built the logistic growth model and compared their accuracy with the R2 coefficient measure. Based on the lockdown periods and severe protection measures, a scenario-based analysis of four different SIR models predicts the confirmed cases. This proposed scenario-based analysis is helpful to pre-estimate the maximum infection rate and maximum peak day of infection with the total percentage of the population being infected by the COVID-19 outbreak in India. This analysis suggests that the severe control measures are working well in India, despite the exponential growth of the outbreak situation. © 2022 Author(s).