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Mathematical model for the novel coronavirus (2019-nCOV) with clinical data using fractional operator.

Ahmed M A El-SayedAnas ArafaAhmed Hagag
Published in: Numerical methods for partial differential equations (2022)
Coronavirus infection (COVID-19) is a considerably dangerous disease with a high demise rate around the world. There is no known vaccination or medicine until our time because the unknown aspects of the virus are more significant than our theoretical and experimental knowledge. One of the most effective strategies for comprehending and controlling the spread of this epidemic is to model it using a powerful mathematical model. However, mathematical modeling with a fractional operator can provide explanations for the disease's possibility and severity. Accordingly, basic information will be provided to identify the kind of measure and intrusion that will be required to control the disease's progress. In this study, we propose using a fractional-order SEIARPQ model with the Caputo sense to model the coronavirus (COVID-19) pandemic, which has never been done before in the literature. The stability analysis, existence, uniqueness theorems, and numerical solutions of such a model are displayed. All results were numerically simulated using MATLAB programming. The current study supports the applicability and influence of fractional operators on real-world problems.
Keyphrases
  • sars cov
  • healthcare
  • coronavirus disease
  • mental health
  • social media
  • respiratory syndrome coronavirus
  • machine learning
  • health information
  • artificial intelligence
  • deep learning