COVID-19, the infectious disease caused by the most recently discovered coronavirus is related to the upper respiratory tract family of disorders. It triggers asthma, severe respiratory diseases, cause lung infection and bronchiolitis infections. Though the severity of these infections are getting obsolete but may remain in the mild forms of waves in our lives. A thorough study about its spread across the globe, its prediction and understanding the transmission patterns, through various statistical models might be one of the effective ways to provide an insight to various aspects of the disease and suggest prevention strategies. In the light of this, Auto Regression (AR) models are developed for the confirmed cases with 5 days lag, in 6 different states of India. The data has been trained from July 2020 to July 2023 taking into account the three most impactful corona waves. August 2022 data has been used for testing & validating the models. Based on the population size and total number of confirmed cases the Indian states have been classified into three categories: Most affected, moderately affected & least affected states. Two states have been selected in each of these categories for the purpose of research study here. Auto Regression models are developed for the purpose of prediction in each of the states for all the 3 waves. Finally, the prediction of fourth wave is done for the month of July 2022 by using the third wave AR models. The results varies from state to state for each AR model.

Kokila Ramesh

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Three waves of COVID-19 in India-An Autoregression Model