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1.
Fractals ; 30(8), 2022.
Article in English | Scopus | ID: covidwho-2194025

ABSTRACT

Currently, the entire planet is suffering from a contagious epidemic infection, 2019-nCOV due to newly detected coronavirus. This is a lethal infectious virus that has destroyed thousands of lives all over the world. The important aim of this study is to investigate a susceptible-infected-treatment-recovered (SITR) model of coronavirus (2019-nCOV) with bi-modal virus spread in a susceptible population. The considered 2019-nCOV model is analyzed by two fractional derivatives: the Caputo and Atangana-Baleanu-Caputo (ABC). For the Caputo model, we present a few basic mathematical characteristics such as existence, positivity, boundedness and stability result for disease-free equilibria. The fixed-point principle is used to establish the existence and uniqueness conditions for the ABC model solution. We employed the Adams-Bashforth-Moulton (ABM) numerical technique for the Caputo model solution and the Toufik-Atangana (TA) numerical approach for the ABC model solution. Finally, using MATLAB, the simulation results are shown to highlight the impact of arbitrarily chosen fractional-order and model parameters on infection dynamics. © 2022 The Author(s).

2.
Chaos Solitons & Fractals ; 138:11, 2020.
Article in English | Web of Science | ID: covidwho-1174129

ABSTRACT

a mathematical model depicting the spread of covid-19 epidemic and implementation of population covid-19 intervention in Italy. The model has 8 components leading to system of 8 ordinary differential equations. In this paper, we investigate the model using the concept of fractional differential operator. A numerical method based on the Lagrange polynomial was used to solve the system equations depicting the spread of COVID-19. A detailed investigation of stability including reproductive number using the next generation matrix, and the Lyapunov were presented in detail. Numerical simulations are depicted for various fractional orders. (C) 2020 Elsevier Ltd. All rights reserved.

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