Second Wave COVID-19 Predictions and Forecasting of Confirmed Cases in West Bengal Using ARIMA Model
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)
INTRODUCTION
COVID-19 brought on by the SARS-COV-2 virus [1] became a cause of global disaster. In
December 2019, the virus initially appeared in the province of Hubei, Wuhan, China. In less than a
month, what started out as a few cases of pneumonia in Wuhan with no known cause, became a global disaster. More than 300,000 individuals have lost their lives and over 6 million individuals have been affected globally. In order to stop the sickness from spreading, nations have effectively been shut down, public spaces have been restricted, and several additional activity-restricting regulations have been put in place [2, 3]. The primary way of transmission of COVID-19 virus is by droplets that
are expelled from a person’s mouth or nose while coughing or sneezing [4]. If individuals are
cautious and avoid coughing or sneezing carelessly, it might not seem lethal, but the fact that COVID19 has spread around the world refutes the idea that it cannot be viewed as fatal [5–7].
Keyworde: COVID-19, forecasting model, autocorrelation function (ACF), partial autocorrelation function (PACF), autoregressive integrated moving average (ARIMA)
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