Outbreak Prediction of COVID-19 Patients for Dense and Populated Countries Using Machine Learning
14 Pages Posted: 30 Jul 2020
Date Written: July 19, 2020
The Coronavirus Disease-2019 (COVID-19) pandemic continues to have a devastating effect on the health and well-being of the global population. An increase in the number of patients testing positive for COVID-19 has created a lot of stress on governing bodies across the globe and they are finding it difficult to tackle the situation. We have developed an outbreak prediction system for COVID-19 for the top 10 highly and densely populated countries worldwide. Our prediction model forecasts the count of the new cases likely to arise for the next 5 days using 9 different machine learning algorithms. A suitable model for predicting the rise in the new cases has been highlighted for most of the countries having an average accuracy of more than 90 \%. The highest accuracy that we achieved was 99.93%. Our prediction model can help the stakeholders to be prepared in advance for such an outbreak to ensure the proper management of the available resources.
Note: Funding: No funding was involved in the present work.
Conflict of Interest: Authors A. Khakharia, A. Tiwari, J. Shah, P. Daphal, S. Jain, V. Shah, M.Warang and N. Mehendale, declare that he has no conflict of interest.
Ethical Approval: This article does not contain any studies with animals or Humans performed by any of the authors. All the necessary permissions were obtained from the Institute Ethical Committee and concerned authorities.
Keywords: COVID-19 outbreak prediction, COVID-19, Machine learning
JEL Classification: I
Suggested Citation: Suggested Citation