Next Article in Journal
Shoes and Insoles: The Influence on Motor Tasks Related to Walking Gait Variability and Stability
Previous Article in Journal
Connectivity as a Mediating Mechanism in the Cybervictimization Process
Open AccessArticle

Predicting the Epidemiological Outbreak of the Coronavirus Disease 2019 (COVID-19) in Saudi Arabia

1
Computer Science Department, College of Science and Humanities in Jubail, Imam Abdulrahman Bin Faisal University, Jubail P.O. Box 31961, Saudi Arabia
2
Department of Engineering and Mathematics, Sheffield Hallam University, Sheffield S1 1WB, UK
3
Computer Science and Information Department, College of Computer Science and Engineering, University of Ha’il, Hail 8145, Saudi Arabia
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(12), 4568; https://doi.org/10.3390/ijerph17124568
Received: 26 April 2020 / Revised: 18 May 2020 / Accepted: 20 June 2020 / Published: 25 June 2020
The coronavirus diseases 2019 (COVID-19) outbreak continues to spread rapidly across the world and has been declared as pandemic by World Health Organization (WHO). Saudi Arabia was among the countries that was affected by the deadly and contagious virus. Using a real-time data from 2 March 2020 to 15 May 2020 collected from Saudi Ministry of Health, we aimed to give a local prediction of the epidemic in Saudi Arabia. We used two models: the Logistic Growth and the Susceptible-Infected-Recovered for real-time forecasting the confirmed cases of COVID-19 across Saudi Arabia. Our models predicted that the epidemics of COVID-19 will have total cases of 69,000 to 79,000 cases. The simulations also predicted that the outbreak will entering the final-phase by end of June 2020. View Full-Text
Keywords: 2019 novel coronavirus; COVID-19; Saudi Arabia; logistic growth model; SIR model 2019 novel coronavirus; COVID-19; Saudi Arabia; logistic growth model; SIR model
Show Figures

Figure 1

MDPI and ACS Style

Alboaneen, D.; Pranggono, B.; Alshammari, D.; Alqahtani, N.; Alyaffer, R. Predicting the Epidemiological Outbreak of the Coronavirus Disease 2019 (COVID-19) in Saudi Arabia. Int. J. Environ. Res. Public Health 2020, 17, 4568.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop