Statistical analysis of national & municipal corporation level database of COVID-19 cases In India

Bajaj, N. S.; Pardeshi, S. S.; Patange, A. D.; Kotecha, D.; Mate, K. K.

Since its origin in December 2019, Novel Coronavirus or COVID-19 has caused massive panic in the word by infecting millions of people with a varying fatality rate. The main objective of Governments worldwide is to control the extent of the outbreak until a vaccine or cure has been devised. Machine learning has been an efficient mechanism to train, map, analyze, and predict datasets. This paper aims to utilize regression, a supervised machine learning algorithm to assess time-series datasets of COVID-19 pandemic by performing comparative analysis on datasets of India and two Municipal Corporations of Maharashtra, namely, Mira-Bhayander and Akola. This study's current contribution is an attempt towards drawing attention to the dynamics of the pandemic in a controlled locality such as Municipal Corporation. The results of the current study depicts that growth of COVID-19 cases is exponential when considered nationally, however, for limited area the nature of curve is observed to be cubic for total cases and multi-peak Gaussian for active cases. In conclusion, Government should empower district/ corporations to adopt their own methodology and decisionmaking policy to contain the pandemic at regional-level like in the case of Dharavi.