ISSN : 2663-2187

A Mathematical Approach for Assessing the Effect of Treatment Modalities on Tuberculosis Dynamics

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Naresh Kumar Jothi, Lakshmi.Senthil kumar P
ยป doi: 10.48047/AFJBS.6.Si2.2024.6069-6087

Abstract

In this paper, we examined the mechanism of Mycobacterium tuberculosis disease. Airborne tuberculosis is a disease that is putting the world's human beings at risk. This model carried out six-dimensional compartments represent the susceptible individual, latently exposed individual, individual infected at home, individual infected in at public place, individual infected at the hospital and the rate of recovered class. In this model, we described all compartments of the transmissible illness of Mycobacterium tuberculosis (MT) and how its spread in general population communities. The genus Mycobacterium is believed to have evolved more than 150 million years ago; to lower the prevalence of infectious cases in the community, our theoretical framework proposed a strategy for preventing and controlling tuberculosis infections. In our model tuberculosis is created that involves three types of medication:, individual treatment at home, individual treatment at a general ayurvedic health care provider and individual treatment at a hospital. We find out the basic reproduction number ????0. The disease-free population is globally asymptotically stable if ????0 < 1 and the equilibrium between endemics is globally asymptotically stable if ????0 > 1. Our model demonstrates the significant detrimental effect of home treatment and individual treatment at the hospital and Individual people who have been infected in public get cured by taking medication. The Lyapunov function is used to derive the TB disease in the community is globally asymptotically stable. We used a Jacobian matrix to examine local stability and diagonal stability. By using the Routh-Hurwitz criteria, we analysed the local stability of cubic polynomials. We derived sustainable and non-negatively feasible solutions. We used random values in MATLAB to simulate the result of the model.

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