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Second Wave COVID-19 Predictions and Forecasting of Confirmed Cases in West Bengal Using ARIMA Model

Sumanta Dey, Abhishek Saha, Pijush Dutta, Gour Gopal Jana

Abstract


Infection and death rates surged drastically during the second wave of the COVID-19 (called delta variant) in India, owing to the destructive virus. As our country's economic load makes it more difficult to control the measures and it is critical for states such as West Bengal to forecast future cases. The present study introduced a time series forecasting model aimed at predicting and forecasting the number of confirmed and active COVID-19 cases up until July 2021. For the application of model dataset was taken from the Public Health Department in West Bengal, India. An Autoregressive integrated moving average-ARIMA (2,1,2) time series model was used to estimate the expected daily number of COVID-19 cases from April 18 to July 13, 2021. From the result analysis it was shown that confirmed cases in Bengal will be 827±200 by the end of July (July 14, 2021 to July 27, 2021) based on our forecasts which was quite satisfactory with real phenomenon. The findings of the present paper was used to forecast an increase in daily cases in West Bengal over the next month, which can assist the government in developing actions to stop the spread of virus.

Keywords


COVID-19, forecasting model, autocorrelation function (ACF), partial autocorrelation function (PACF), autoregressive integrated moving average (ARIMA)

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