A New Dynamical Analysis of COVID-19 Epidemic Model Using Two Fractional Operators


== Abstract ==

Fractional calculus has emerged as a powerful tool for modeling complex systems with memory and hereditary properties, particularly in biological and epidemiological contexts. Despite its potential, accurately capturing the dynamics of diseases like COVID-19 remains challenging due to the need for models that balance accuracy with computational efficiency. This study presents a new dynamic analysis of the fractional-order coronavirus (2019-nCOV) pandemic model. The model incorporates two fractional derivatives, the Caputo and Atangana-Baleanu in Caputo sense (ABC) derivatives. By applying the Fractional Temimi-Ansari Method (FTAM), we derive a power series solution, demonstrating the existence, uniqueness, and convergence of the solutions. Our findings indicate that the fractional derivatives, particularly the ABC derivative, offer a more comprehensive description of memory effects in biological systems, which is crucial for accurately modeling the dynamics of COVID-19. The results show a high degree of accuracy and efficiency in capturing the behavior of the system, with convergence analyses confirming the robustness of the model. Graphical representations further illustrate the system’s behavior under different parameter settings. The proposed model also effectively simulates the spread of the virus in Ghana, offering valuable insights for implementing non-pharmaceutical interventions. These findings demonstrate the potential of fractional calculus in improving epidemic models, especially in capturing the long-term effects and memory characteristics of pandemics.OPEN ACCESS Received: 31/08/2024 Accepted: 01/11/2024

== Full document ==
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