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 language | English |
|---|---|
| Pages (from-to) | 43-61 |
| Number of pages | 19 |
| Journal | Progress in Fractional Differentiation and Applications |
| Volume | 7 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2021 |
Keywords
- Coronavirus
- Delay differential models
- Fractional calculus
- Immunological barrier
- Infectious disease
- Sensitivity
ASJC Scopus subject areas
- Analysis
- Applied Mathematics
