A novel fractional order model of SARS-CoV-2 and Cholera disease with real data

Fatma Özköse; Rafla Habbireeh; M Tamer Şenel

doi:10.1016/j.cam.2022.114969

A novel fractional order model of SARS-CoV-2 and Cholera disease with real data

J Comput Appl Math. 2023 May 15:423:114969. doi: 10.1016/j.cam.2022.114969. Epub 2022 Dec 1.

Authors

Fatma Özköse¹, Rafla Habbireeh^{2

3}, M Tamer Şenel¹

Affiliations

¹ Erciyes University, Department of Mathematics, Faculty of Science, Kayseri, Türkiye.
² Institute of Science, Erciyes University, Kayseri 38039, Türkiye.
³ Department of Mathematics, Faculty of Science, Misurata University, Misurata, Libya.

Abstract

This study presents a novel approach to investigating COVID-19 and Cholera disease. In this situation, a fractional-order model is created to investigate the COVID-19 and Cholera outbreaks in Congo. The existence, uniqueness, positivity, and boundedness of the solution are studied. The equilibrium points and their stability conditions are achieved. Subsequently, the basic reproduction number (the virus transmission coefficient) is calculated that simply refers to the number of people, to whom an infected person can make infected, as $R_{0} = 6.7442389 e - 10$ by using the next generation matrix method. Next, the sensitivity analysis of the parameters is performed according to $R_{0}$ . To determine the values of the parameters in the model, the least squares curve fitting method is utilized. A total of 22 parameter values in the model are estimated by using real Cholera data from Congo. Finally, to find out the dynamic behavior of the system, numerical simulations are presented. The outcome of the study indicates that the severity of the Cholera epidemic cases will decrease with the decrease in cases of COVID-19, through the implementation and follow-up of safety measures that have been taken to reduce COVID-19 cases.

Keywords: Fractional-order derivative; Parameter estimation; Real data; SARS-CoV-2 and Cholera disease; Sensitivity analysis; Stability analysis.