A model for the dynamics of COVID-19 infection transmission in human with latent delay

Abstract

In this research, we have derived a mathematical model for within human dynamics of COVID-19 infection using delay differential equations. The new model considers a 'latent period' and 'the time for immune response' as delay parameters, allowing us to study the effects of time delays in human COVID-19 infection. We have determined the equilibrium points and analyzed their stability. The disease-free equilibrium is stable when the basic reproduction number, $R_0$, is below unity. Stability switch of the endemic equilibrium occurs through Hopf-bifurcation. This study shows that the effect of latent delay is stabilizing whereas immune response delay has a destabilizing nature.

This is a preprint of a paper whose final and definite form is published in 'Afrika Matematika' at [https://doi.org/10.1007/s13370-024-01226-0]

References in corpus (4)

• Fractional model of COVID-19 applied to Galicia, Spain and Portugal
• Pest control using farming awareness: impact of time delays and optimal use of biopesticides
• Modeling and Forecasting of COVID-19 Spreading by Delayed Stochastic Differential Equations
• A stochastic time-delayed model for the effectiveness of Moroccan COVID-19 deconfinement strategy