This study aims to structure and evaluate a newCOVID-19modelwhich predicts vaccination effect in theKingdom of Saudi Arabia(KSA)under Atangana-Baleanu-Caputo(ABC)fractional derivatives.On the statistical aspect,we ana...This study aims to structure and evaluate a newCOVID-19modelwhich predicts vaccination effect in theKingdom of Saudi Arabia(KSA)under Atangana-Baleanu-Caputo(ABC)fractional derivatives.On the statistical aspect,we analyze the collected statistical data of fully vaccinated people from June 01,2021,to February 15,2022.Then we apply the Eviews program to find the best model for predicting the vaccination against this pandemic,based on daily series data from February 16,2022,to April 15,2022.The results of data analysis show that the appropriate model is autoregressive integratedmoving average ARIMA(1,1,2),and hence,a forecast about the evolution of the COVID-19 vaccination in 60 days is presented.The theoretical aspect provides equilibrium points,reproduction number R0,and biologically feasible region of the proposed model.Also,we obtain the existence and uniqueness results by using the Picard-Lindel method and the iterative scheme with the Laplace transform.On the numerical aspect,we apply the generalized scheme of the Adams-Bashforth technique in order to simulate the fractional model.Moreover,numerical simulations are performed dependent on real data of COVID-19 in KSA to show the plots of the effects of the fractional-order operator with the anticipation that the suggested model approximation will be better than that of the established traditional model.Finally,the concerned numerical simulations are compared with the exact real available date given in the statistical aspect.展开更多
基金supported by the Deanship of Scientific Research,Imam Mohammad Ibn Saud Islamic University (IMSIU),Saudi Arabia,Grant No. (21-13-18-069).
文摘This study aims to structure and evaluate a newCOVID-19modelwhich predicts vaccination effect in theKingdom of Saudi Arabia(KSA)under Atangana-Baleanu-Caputo(ABC)fractional derivatives.On the statistical aspect,we analyze the collected statistical data of fully vaccinated people from June 01,2021,to February 15,2022.Then we apply the Eviews program to find the best model for predicting the vaccination against this pandemic,based on daily series data from February 16,2022,to April 15,2022.The results of data analysis show that the appropriate model is autoregressive integratedmoving average ARIMA(1,1,2),and hence,a forecast about the evolution of the COVID-19 vaccination in 60 days is presented.The theoretical aspect provides equilibrium points,reproduction number R0,and biologically feasible region of the proposed model.Also,we obtain the existence and uniqueness results by using the Picard-Lindel method and the iterative scheme with the Laplace transform.On the numerical aspect,we apply the generalized scheme of the Adams-Bashforth technique in order to simulate the fractional model.Moreover,numerical simulations are performed dependent on real data of COVID-19 in KSA to show the plots of the effects of the fractional-order operator with the anticipation that the suggested model approximation will be better than that of the established traditional model.Finally,the concerned numerical simulations are compared with the exact real available date given in the statistical aspect.
