COVID-19 Epidemic Analysis and Prediction in Virudhunagar District Using Machine Learning

Shanmuga Eswari, M.; Indumathi, N.; Ramalakshmi, R.

In this era, the universe is facing the new pandemic situation. Every person feared about this new situation and new virus. That virus is named as COVID-19. This Corona virus is impinge on respiratory and leads to fatal. But this virus is connected to the same family of corona viruses such as Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MARS). The mortal rate is sky-scraping when compared to previous SARS-COV with fatal rate of 10% and MARS-COV with rate of 30% of world population. The proposed covid-19 study gives the impression of being up rural place of Tamil nadu’s Virudhunagar district in India. This analysis has been taken between the pandemic lockdown period of March 13 and July 26 of 2020. This study has shown the infectious growth rate in Virudhunagar and Sivakasi during the above mentioned outbreak time of 0.01754, 0.036643 respectively in the overall population. In Sivakasi, the Covid-19 spreading rate is high of 22.47% and death rate of 32.55% compared to other taluk in Virudhunagar. The morality age was an average of 61.5. This learning is implemented simple k-nearest neighbor and optimizable k-nearest neighbor classifier for predicting the pandemic situation in Virudhunagar district. Acquired an accuracy of 94.09% and 98.06% and the performance metric of Area Under Curve of Receiver Operating Characteristic according to 0.88,0.94 and respectively. This has been shown the corona virus affected the old age and pre medical conditioned existing people. This study is providing assistance to welfare department for taking safety measures as well as, public to get motivation to keep them safe. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.