A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is
In response to the global COVID-19 pandemic, this work aims to understand the early time evolution and the spread of the disease outbreak with a data driven approach. To this effect, we applied Susceptible- Infective-Recovered/Removed (SIR) epidemiological model on the disease. Additionally, we used the Machine Learning linear regression model on the historical COVID-19 data to predict the earlier stage of the disease. The evolution of the disease spread with the Mathematical SIR model anddoi:10.34257/gjsfrfvol20is5pg19 fatcat:xlbo2wfqpfg3lkhoh7la6xsplq