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Using Susceptible-Exposed-Infectious-Recovered Model to Forecast Coronavirus Outbreak

Debabrata Dansana1, Raghvendra Kumar1, Arupa Parida1, Rohit Sharma2, Janmejoy Das Adhikari1, Hiep Van Le3,*, Binh Thai Pham4, Krishna Kant Singh5, Biswajeet Pradhan6,7,8,9

1 Department of Computer Science and Engineering, GIET University, Gunupur, Odisha, India
2 Department of Electronics & Communication Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, NCR Campus, Delhi-NCR Campus, Modinagar, Ghaziabad, India
3 Institute of Research and Development, Duy Tan University, Da Nang, 550000, Viet Nam
4 University of Transport Technology, Hanoi, 100000, Viet Nam
5 Department of ECE, KIET Group of Institutions, Ghaziabad, India
6 Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), University of Technology Sydney, Sydney, NSW, 2007, Australia
7 Department of Energy and Mineral Resources Engineering, Sejong University, Seoul, 05006, Korea
8 Center of Excellence for Climate Change Research, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
9 Earth Observation Center, Institute of Climate Change, Universiti Kebangsaan Malaysia, 43600, Selangor, Malaysia

* Corresponding Author: Hiep Van Le. Email: email

(This article belongs to the Special Issue: COVID-19 impacts on Software Engineering industry and research community)

Computers, Materials & Continua 2021, 67(2), 1595-1612. https://doi.org/10.32604/cmc.2021.012646

Abstract

The Coronavirus disease 2019 (COVID-19) outbreak was first discovered in Wuhan, China, and it has since spread to more than 200 countries. The World Health Organization proclaimed COVID-19 a public health emergency of international concern on January 30, 2020. Normally, a quickly spreading infection that could jeopardize the well-being of countless individuals requires prompt action to forestall the malady in a timely manner. COVID-19 is a major threat worldwide due to its ability to rapidly spread. No vaccines are yet available for COVID-19. The objective of this paper is to examine the worldwide COVID-19 pandemic, specifically studying Hubei Province, China; Taiwan; South Korea; Japan; and Italy, in terms of exposed, infected, recovered/deceased, original confirmed cases, and predict confirmed cases in specific countries by using the susceptible-exposed-infectious-recovered model to predict the future outbreak of COVID-19. We applied four differential equations to calculate the number of confirmed cases in each country, plotted them on a graph, and then applied polynomial regression with the logic of multiple linear regression to predict the further spread of the pandemic. We also compared the calculated and predicted cases of confirmed population and plotted them in the graph, where we could see that the lines of calculated and predicted cases do intersect with each other to give the perfect true results for the future spread of the virus. This study considered the cases from 22 January 2020 to 25 April 2020.

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APA Style
Dansana, D., Kumar, R., Parida, A., Sharma, R., Adhikari, J.D. et al. (2021). Using susceptible-exposed-infectious-recovered model to forecast coronavirus outbreak. Computers, Materials & Continua, 67(2), 1595-1612. https://doi.org/10.32604/cmc.2021.012646
Vancouver Style
Dansana D, Kumar R, Parida A, Sharma R, Adhikari JD, Le HV, et al. Using susceptible-exposed-infectious-recovered model to forecast coronavirus outbreak. Comput Mater Contin. 2021;67(2):1595-1612 https://doi.org/10.32604/cmc.2021.012646
IEEE Style
D. Dansana et al., "Using Susceptible-Exposed-Infectious-Recovered Model to Forecast Coronavirus Outbreak," Comput. Mater. Contin., vol. 67, no. 2, pp. 1595-1612. 2021. https://doi.org/10.32604/cmc.2021.012646



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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