Hybrid Method for Simulation of a Fractional COVID-19 Model with Real Case Application

In this research, we provide a mathematical analysis for the novel coronavirus responsible for COVID-19, which continues to be a big source of threat for humanity. Our fractional-order analysis is carried out using a non-singular kernel type operator known as the Atangana-Baleanu-Caputo (ABC) deriva...

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Bibliographic Details
Published in:Axioms 2021-12, Vol.10 (4), p.290
Main Authors: Din, Anwarud, Khan, Amir, Zeb, Anwar, Sidi Ammi, Moulay Rchid, Tilioua, Mouhcine, Torres, Delfim F. M.
Format: Article
Language:English
Subjects:
ABC derivative
Algorithms
coronavirus disease 2019 (COVID-19)
Coronaviruses
COVID-19
Decomposition
Disease transmission
existence analysis
hybrid method
Infections
Mathematical models
Parameter sensitivity
Population
Quarantine
Respiratory diseases
semi-analytical solution
Sensitivity analysis
Severe acute respiratory syndrome coronavirus 2
Variables
Viral diseases
Viruses
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Summary:In this research, we provide a mathematical analysis for the novel coronavirus responsible for COVID-19, which continues to be a big source of threat for humanity. Our fractional-order analysis is carried out using a non-singular kernel type operator known as the Atangana-Baleanu-Caputo (ABC) derivative. We parametrize the model adopting available information of the disease from Pakistan in the period 9 April to 2 June 2020. We obtain the required solution with the help of a hybrid method, which is a combination of the decomposition method and the Laplace transform. Furthermore, a sensitivity analysis is carried out to evaluate the parameters that are more sensitive to the basic reproduction number of the model. Our results are compared with the real data of Pakistan and numerical plots are presented at various fractional orders.
ISSN:2075-1680
2075-1680
DOI:10.3390/axioms10040290