Abstract
This manuscript is devoted to investigating a fractional-order mathematical model of COVID-19. The corresponding derivative is taken in Caputo sense with power-law of fractional order μ and fractal dimension χ. We give some detailed analysis on the existence and uniqueness of the solution to the proposed problem. Furthermore, some results regarding basic reproduction number and stability are given. For the proposed theoretical analysis, we use fixed point theory while for numerical analysis fractional Adams–Bashforth iterative techniques are utilized. Using our numerical scheme is verified by using some real values of the parameters to plot the approximate solution to the considered model. Graphical presentations corresponding to different values of fractional order and fractal dimensions are given. Moreover, we provide some information regarding the real data of Saudi Arabia from 1 March 2020 till 22 April 2021, then calculated the fatality rates by utilizing the SPSS, Eviews and Expert Modeler procedure. We also built forecasts of infection for the period 23 April 2021 to 30 May 2021, with 95% confidence.
Highlights
We have provided an excellent fit to the reported cases and estimated the model parameters to explore the transmission dynamics 2 of this novel infection
We have seen that it is on the ascent, as the affirmed cases expanded from 1563 in March with an average of 50 cases in a day, at that point expanded during April to reach 19,839 with an average of 661 cases
We have presented the numerical results graphically by using various fractional order derivatives and different values of fractal dimension
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. We remark that some countries have succeeded in creating COVID-19 vaccines including USA, UK, Germany, China, etc This disease spreads rapidly making it one of the most infectious and contagious diseases in today’s world. In [3], Li et al proposed a latency-period pandemic COVID-19 model and adapted the proposed model to report the infected cases in mainland China. In [4], the authors developed a SIR-based COVID19 infection model and implemented the proposed model to explore and forecast the transmission dynamics of this pandemic in China, Italy, and France, which are highly affected countries. The authors in [14] formulated a fractional COVID-19 model using the ABC operator and gave a better approximation of the reported cases in Wuhan.
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