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A fractional order model of the COVID-19 outbreak in Bangladesh


  • Received: 13 August 2022 Revised: 07 November 2022 Accepted: 08 November 2022 Published: 24 November 2022
  • In this study, we propose a Caputo-based fractional compartmental model for the dynamics of the novel COVID-19. The dynamical attitude and numerical simulations of the proposed fractional model are observed. We find the basic reproduction number using the next-generation matrix. The existence and uniqueness of the solutions of the model are investigated. Furthermore, we analyze the stability of the model in the context of Ulam-Hyers stability criteria. The effective numerical scheme called the fractional Euler method has been employed to analyze the approximate solution and dynamical behavior of the model under consideration. Finally, numerical simulations show that we obtain an effective combination of theoretical and numerical results. The numerical results indicate that the infected curve predicted by this model is in good agreement with the real data of COVID-19 cases.

    Citation: Saima Akter, Zhen Jin. A fractional order model of the COVID-19 outbreak in Bangladesh[J]. Mathematical Biosciences and Engineering, 2023, 20(2): 2544-2565. doi: 10.3934/mbe.2023119

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  • In this study, we propose a Caputo-based fractional compartmental model for the dynamics of the novel COVID-19. The dynamical attitude and numerical simulations of the proposed fractional model are observed. We find the basic reproduction number using the next-generation matrix. The existence and uniqueness of the solutions of the model are investigated. Furthermore, we analyze the stability of the model in the context of Ulam-Hyers stability criteria. The effective numerical scheme called the fractional Euler method has been employed to analyze the approximate solution and dynamical behavior of the model under consideration. Finally, numerical simulations show that we obtain an effective combination of theoretical and numerical results. The numerical results indicate that the infected curve predicted by this model is in good agreement with the real data of COVID-19 cases.



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