Abstract
The COVID-19 disease was first identified in the month of December 2019 in city of Wuhan in China. The infection is caused by severe acute respiratory syndrome shortened as SARS-CoV-2. COVID-19 was reported to the international health organization WHO on December 31, 2019, and the outbreak was declared a global health emergency on January 30, 2020, by WHO. The first case was reported in India from Kerala’s Thrissur in a student returned from University of Wuhan China on January 30, 2020, followed by phenomenal spread in Delhi, Tamil Nadu, Maharashtra and Odisha. The objective of this paper is to predict the number of people getting infected by such virus during any such epidemic or pandemic outbreaks in the future and to diminish the impact of such outbreaks by taking preventive steps including smart health monitoring and spreading awareness of clinicians to provide timely diagnosis and treatment. Accuracy of predictions can be scaled up by using more training data.
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Kumar, M., Mahto, A.K., Afshar Alam, M., Haq, Z.A. (2022). SARS-CoV-2 Prediction of Outbreak and Analysis Using Machine Learning. In: Pandian, A.P., Palanisamy, R., Narayanan, M., Senjyu, T. (eds) Proceedings of Third International Conference on Intelligent Computing, Information and Control Systems. Advances in Intelligent Systems and Computing, vol 1415. Springer, Singapore. https://doi.org/10.1007/978-981-16-7330-6_66
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