AEFCO: A Machine Learning based Covid-19 Epidemic Analysis Dashboard

Abstract

The year 2020 will be known as the hosting year of yet another pandemic, the Covid-19. It's highly contagious and fatal if ignored for a long time. Various pandemics have been seen in World history in which some of them were more dangerous and disastrous than the others to be the humans. We have been living here in a very troublesome time once again and having a war with an invisible enemy; the family of COVID19 coronavirus. This paper is focused on the estimation of the COVID-19 Outbreak in the India. It also includes the analysis of currently available datasets made public by the Govt. of India. The analysis part answers questions like – 'What is the rate of spread?', The increment in the number of patients, number of recoveries and number of deceased on an everyday basis, and the comparative study of the features. The paper is also inclined towards the estimation of its further outbreak in our country. Time series based Machine Learning models have been deployed on these datasets. The product of this project is a Dashboard, which will enable a user to use those models to predict the outbreak further into the future with just a click. The main theme of this paper is to apply different models of machine learning for forecasting of predicted reachability of Coronaviruses across all countries of the world based upon real-time output data from COVID 19 Dashboard which is based on Machine Learning.

Cite as

Kishalay Raj, Shiv Kumar Choubey, Rohit Kumar Sinha, Mohit Kumar, Kamala Pati Tiwary, & Sanjay Kumar Sinha. (2021). AEFCO: A Machine Learning based Covid-19 Epidemic Analysis Dashboard. Journal of Applied Mathematics and Statistical Analysis, 2(2), 1–12. https://doi.org/10.5281/zenodo.5515346