Regression Analysis of COVID-19 Spread in India and its Different States

Linear and polynomial regression model has been used to investigate the COVID-19 outbreak in India and its different states using time series epidemiological data up to 26 ^th May 2020. The data driven analysis shows that the case fatality rate (CFR) for India (3.14% with 95% confidence interval of 3.12% to 3.16%) is half of the global fatality rate, while higher than the CFR of the immediate neighbors i.e . Bangladesh, Pakistan and Sri Lanka. Among Indian states, CFR of West Bengal (8.70%, CI: 8.21–9.18%) and Gujrat (6.05%, CI: 4.90–7.19%) is estimated to be higher than national rate, whereas CFR of Bihar, Odisha and Tamil Nadu is less than 1%. The polynomial regression model for India and its different states is trained with data from 21 ^st March 2020 to 19 ^th May 2020 (60 days). The performance of the model is estimated using test data of 7 days from 20 ^th May 2020 to 26 ^th May 2020 by calculating RMSE and % error. The model is then used to predict number of patients in India and its different states up to 16 ^th June 2020 (21 days). Based on the polynomial regression analysis, Maharashtra, Gujrat, Delhi and Tamil Nadu are continue to remain most affected states in India.