A fractional-order model for CoViD-19 dynamics with reinfection and the importance of quarantine

TL;DR

This paper introduces a fractional-order mathematical model for CoViD-19 that accounts for reinfection and quarantine, providing insights into disease dynamics and potential control strategies.

Contribution

It presents a novel non-integer order model incorporating reinfection and quarantine effects, enhancing understanding of CoViD-19 spread and control.

Findings

Reinfection significantly impacts disease dynamics.

Fractional-order derivatives improve model accuracy.

Quarantine measures influence infection trajectories.

Abstract

Coronavirus disease 2019 (CoViD-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Among many symptoms, cough, fever and tiredness are the most common. People over 60 years old and with associated comorbidities are most likely to develop a worsening health condition. This paper proposes a non-integer order model to describe the dynamics of CoViD-19 in a standard population. The model incorporates the reinfection rate in the individuals recovered from the disease. Numerical simulations are performed for different values of the order of the fractional derivative and of reinfection rate. The results are discussed from a biological point of view.