Modeling and simulation: a study on predicting the outbreak of COVID-19 in Saudi Arabia
type: Item
instance of: scholarly article
title: Modeling and simulation: a study on predicting the outbreak of COVID-19 in Saudi Arabia
zbMATH Open document ID: 1471.92336
DOI: 10.1155/2021/5522928
author: Mutum Zico
author: Idir Mechai
author: Abdullah Ali H. Ahmadini
author: Ahmed Hussein Msmali
published in: Discrete Dynamics in Nature and Society
publication date: 2021-08-12T00:00:00Z
review text: Summary: The novel coronavirus disease (COVID-19) has resulted in an ongoing pandemic affecting the health system and economy of more than 200 countries worldwide. Mathematical models are used to predict the biological and epidemiological tendencies of an epidemic and to develop methods for controlling it. In this work, we use a mathematical model perspective to study the role of behavior change in slowing the spread of COVID-19 in Saudi Arabia. The real-time updated data from March 2, 2020, to January 8, 2021, were collected from the Saudi Ministry of Health, aiming to provide dynamic behaviors of the epidemic in Saudi Arabia. During this period, 363,692 people were infected, resulting in 6293 deaths, with a mortality rate of 1.73\%. There was a weak positive relationship between the spread of infection and mortality (\(R^2 = 0.459\)). We used the susceptible-exposed-infection-recovered (SEIR) model, a logistic growth model, with a special focus on the exposed, infected, and recovered individuals to simulate the final phase of the outbreak. The results indicate that social distancing, hygienic conditions, and travel limitations are crucial measures to prevent further spread of the epidemic.
Mathematics Subject Classification ID: 92D30
zbMATH DE Number: 7381268
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2021/5522928
OpenAlex ID: W3173409798
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description: scientific article; zbMATH DE number 7381268