Abstract The capacity to forecast the pandemic growth has been crucial in making decisions on how to combat and control COVID-19 spread in current and future waves of infection. Since the phenomenon was developed over time, we have analyzed the COVID-19 confirmed, recovered, and death cases in Indian provinces through time series analysis to comprehend the growth patterns of these cases. For a better explanation and prediction of COVID-19 dissemination, we have used the well-known ARIMA(Auto Regressive Integrated Moving Average) time series model. The COVID-19 cases from Jan 31, 2020, to Jan 30, 2022, having three waves of Alpha, Delta, and Omicron variants of SARS-CoV-2 were analyzed through time series regression models in India for all 28 states (provinces) and 8 union territories (directly federally governed territories). The analysis could aid in the development of more effective intervention programs and the mitigation of the current and future waves of the pandemic. AMS Classification 37M10 Time series analysis of dynamical systems 62M10 Time series, auto-correlation, regression, etc. in statistics
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Yadav et al. (2024) studied this question.
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