COVID-19 Epidemic Analysis using Machine Learning and Deep Learning Algorithms

Narinder Singh Punn; Sanjay Kumar Sonbhadra; Sonali Agarwal

The copyright holder for this preprint . https://doi.org/10.1101/2020.04.08.20057679 doi: medRxiv preprint on this better surveillance and control activities can be planned [14] . In recent research work, Singer analyzed data of 25 infected counties to follow short term predictions about the COVID 2019 outbreak. The research highlighted that the location-specific rate of disease spread follows either steady or explosive power-law growth with different scaling exponents. With this understanding, the authors analyzed the impact of lockdown in various parts of the world [15] . Based on the above literature, it is evident that sufficient work is available on exploratory data analysis to understand the existing trend of the epidemic but still there is a lot of scopes to develop and test efficient machine learning based prediction models so that proactive strategies could be identified to cater the immediate needs.