A Mathematical Model to Investigate the Transmission of COVID-19 in the Kingdom of Saudi Arabia

Alshammari, Fehaid Salem

doi:10.1155/2020/9136157

Cited by 24 publications

(19 citation statements)

References 19 publications

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“…It is not difficult to write the reproduction number for the disease-free equilibrium point of Eq. ( 12 ) as [ 5 ] …”

Section: Mathematical Model and Discussionmentioning

confidence: 99%

“…Regarding COVID-19, from the initial spread of COVID-19, many of the known mathematical models were used, or newly established by many researchers, For example Giordano et al in [ 4 ] proposed the so called SIDARTHE model and concluded that restrictive social-distancing measures will need to be combined with widespread testing and contact tracing to end the ongoing COVID-19 pandemic. At a same time, Alshammari [ 5 ] proposed the SEYNHR compartmental model and applied real data for Saudi Arabia and obtained good predictions on a short term. The role of quarantining and isolation to control the spread of COVID-19 is studied by Memon et al [ 6 ], where they used an extended SIR model.…”

Section: Introductionmentioning

confidence: 99%

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Complex mathematical SIR model for spreading of COVID-19 virus with Mittag-Leffler kernel

Akyıldız

Alshammari

2021

Adv Differ Equ

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This paper investigates a new model on coronavirus-19 disease (COVID-19), that is complex fractional SIR epidemic model with a nonstandard nonlinear incidence rate and a recovery, where derivative operator with Mittag-Leffler kernel in the Caputo sense (ABC). The model has two equilibrium points when the basic reproduction number $R_{0} > 1$ R 0 > 1 ; a disease-free equilibrium $E_{0}$ E 0 and a disease endemic equilibrium $E_{1}$ E 1 . The disease-free equilibrium stage is locally and globally asymptotically stable when the basic reproduction number $R_{0} <1$ R 0 < 1 , we show that the endemic equilibrium state is locally asymptotically stable if $R_{0} > 1$ R 0 > 1 . We also prove the existence and uniqueness of the solution for the Atangana–Baleanu SIR model by using a fixed-point method. Since the Atangana–Baleanu fractional derivative gives better precise results to the derivative with exponential kernel because of having fractional order, hence, it is a generalized form of the derivative with exponential kernel. The numerical simulations are explored for various values of the fractional order. Finally, the effect of the ABC fractional-order derivative on suspected and infected individuals carefully is examined and compared with the real data.

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“…It is not difficult to write the reproduction number for the disease-free equilibrium point of Eq. ( 12 ) as [ 5 ] …”

Section: Mathematical Model and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Complex mathematical SIR model for spreading of COVID-19 virus with Mittag-Leffler kernel

Akyıldız

Alshammari

2021

Adv Differ Equ

Self Cite

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“…The data is publicly accessible via the COVID-19 dashboard of the Saudi Ministry of Health [27]. The reason we restricted the data to this period is to be able to compare the obtained reproduction number with similar results available in the literature [30,31].…”

Section: Numerical Simulationsmentioning

confidence: 99%

“…Both the infected cases (Figure 2A) and removed cases (Figure 2B) show a reasonable quality of fit. Since the optimization task led to local optima, we were guided by the results reported in [22,30,31] in selecting initial conditions and bounds on the fitted model parameters. The optimum values of model parameters are shown in Table 2.…”

Section: Numerical Simulationsmentioning

confidence: 99%

Dynamics of an SIR-Based COVID-19 Model With Linear Incidence Rate, Nonlinear Removal Rate, and Public Awareness

2021

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The paper studies the dynamics of the classical susceptible-infectious-removed (SIR) model when applied to the transmission of COVID-19 disease. The model includes the classical linear incidence rate but considers a nonlinear removal rate that depends on the hospital-bed population ratio. The model also includes the effects of media on public awareness. We prove that when the basic reproduction number is less than unity the model can exhibit a number of nonlinear phenomena including saddle-node, backward, and Hopf bifurcations. The model is fitted to COVID-19 data pertinent to Saudi Arabia. Numerical simulations are provided to supplement the theoretical analysis and delineate the effects of hospital-bed population ratio and public awareness on the control of the disease.

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“…Since patient zero was discovered, non-confidential data of COVID-19 have been available and free to use to prompt health innovations and digital health technology applications. Many researchers have used the data to model the future of the pandemic or to predict new cases and deaths in the upcoming months [30][31][32][33][34]. Data accessibility has facilitated building models to predict the future of the pandemic in Saudi Arabia and has helped decision-makers to set plans and strategies to fight COVID-19 [35,36].…”

Section: Determinants For Optimising Dhtpsmentioning

confidence: 99%

Optimising Digital Health Platforms in Saudi Arabia: Determinants from the COVID-19 Pandemic Experience

Alghamdi¹,

Alsulayyim²,

Alqahtani³

et al. 2021

Preprint

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COVID-19 poses a significant burden to healthcare systems. Healthcare organisations with a better health innovation infrastructure have faced a reduced burden and achieved success in curbing COVID-19. In Saudi Arabia, digital technologies have played a vital role in fighting SARS-CoV-2 transmission. In this paper, we aimed to summarise the experience of optimising digital health technologies in Saudi Arabia as well as discuss capabilities and opportunities during and beyond the COVID-19 pandemic. A literature review was conducted up to September 2021 to retrieve peer-reviewed articles that critique the use of digital health technology platforms (DHTPs) in Saudi Arabia during the COVID-19 outbreak. A small but significant body of literature examined the digital response to the COVID-19 pandemic in Saudi Arabia. Health officials succeeded in optimising and maintaining a strategy to mitigate the spread of the virus via different digital technologies, such as mobile health applications, artificial intelligence, and machine learning. The quick digital response in Saudi Arabia was facilitated by governmental support and considering users and technology determinants. Future research must concentrate on establishing and updating the guidelines for using DHTPs.

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A Mathematical Model to Investigate the Transmission of COVID-19 in the Kingdom of Saudi Arabia

Cited by 24 publications

References 19 publications

Complex mathematical SIR model for spreading of COVID-19 virus with Mittag-Leffler kernel

Complex mathematical SIR model for spreading of COVID-19 virus with Mittag-Leffler kernel

Dynamics of an SIR-Based COVID-19 Model With Linear Incidence Rate, Nonlinear Removal Rate, and Public Awareness

Optimising Digital Health Platforms in Saudi Arabia: Determinants from the COVID-19 Pandemic Experience

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