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Using Susceptible-Exposed-Infectious-Recovered Model to Forecast Coronavirus Outbreak
Cmc-Computers Materials & Continua ; 67(2):1595-1612, 2021.
Article in English | Web of Science | ID: covidwho-1129916
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.

Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Cmc-Computers Materials & Continua Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Cmc-Computers Materials & Continua Year: 2021 Document Type: Article