Interpreting the COVID-19 infection geospatial data of Indian provinces for Alpha, Delta and Omicron variants using ARIMA and machine learning

The COVID-19 disease wreaked havoc on communities all around the world. The capacity to forecast the pandemic growth has been crucial in making decisions on how to combat it and control its spread in current and future waves of infections. Different mathematical models have recently been employed to anticipate the COVID-19 outbreak globally. We analyzed the COVID-19 confirmed, recovered and deceased cases in India through time series analysis to comprehend the growth patterns of these cases. When the COVID-19 data transitions from one stage to the next, a structural break occurs. We analyzed COVID-19 incidences from Jan 31, 2020, to Jan 30, 2022, having three waves of Alpha, Delta and Omicron variants of SARS-CoV-2 using time series regression and machine learning models in India for all 28 states (provinces) and eight union territories (directly federally governed territories). People should follow the suppressive measures as suggested by the government to break the infection chain. The analysis could aid in the development of more effective intervention programs and the mitigation of the pandemic’s current and future waves.