Dynamics and Sensitivity of Fractional–Order Delay Differential Model For Coronavirus (Covid-19) Infection

Fathalla A. Rihan, Velmurugan Gandhi

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

In this paper, we provide a fractional-order delay differential model for coronavirus (CoV) infection to give us best understand what causes the intensity of symptoms and illness of contaminated lung and respiratory system. A fractional-order and time-delays are incorporated in the model to naturally represent the effects of both long-run and short-run memory in the dynamics of cells and tissues of immune system. Some interesting sufficient conditions that ensure the asymptotic stability of the steady states are obtained. Sensitivity analyses such as sensitivity to variations in the rate of interferon, rate of innate immunity cells, rate of adaptive immunity cells, and variation in pathogen virulence are investigated to provide insight into the role of each and most effective parameter of the model. This consideration may deliver experiences into respiratory infections and define the foremost compelling parameters for treatment

Original languageEnglish
Pages (from-to)43-61
Number of pages19
JournalProgress in Fractional Differentiation and Applications
Volume7
DOIs
Publication statusPublished - Jan 1 2021

Keywords

  • Coronavirus
  • Delay differential models
  • Fractional calculus
  • Immunological barrier
  • Infectious disease
  • Sensitivity

ASJC Scopus subject areas

  • Analysis
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Dynamics and Sensitivity of Fractional–Order Delay Differential Model For Coronavirus (Covid-19) Infection'. Together they form a unique fingerprint.

Cite this