Analysis of a Tuberculosis Infection Model considering the Influence of Saturated Recovery (Treatment)
Author(s) -
Fatima Sulayman,
Farah Aini Abdullah
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/1805651
Subject(s) - bifurcation , tuberculosis , basic reproduction number , mathematics , population , lyapunov function , mycobacterium tuberculosis , stability (learning theory) , stability theory , saturation (graph theory) , hopf bifurcation , computer science , medicine , physics , combinatorics , environmental health , pathology , quantum mechanics , nonlinear system , machine learning
Tuberculosis (TB) is a serious global health threat that is caused by the bacterium Mycobacterium tuberculosis, is extremely infectious, and has a high mortality rate. In this paper, we developed a model of TB infection to predict the impact of saturated recovery. The existence of equilibrium and its stability has been investigated based on the effective reproduction number R C . The model displays interesting dynamics, including backward bifurcation and Hopf bifurcation, which further results in the stable disease-free and stable endemic equilibria to be coexisting. Bifurcation analysis demonstrates that the saturation parameter is accountable for the phenomenon of backward bifurcation. We derive a condition that guarantees that the model is globally asymptotically stable using the Lyapunov function approach to global stability. The numerical simulation also reveals that the extent of saturation of TB infection is the mechanism that is fuelling TB disease in the population.
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