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The Journal of Information and Optimization Sciences (JIOS) is a world leading journal publishing high quality, rigorously peer-reviewed original research in all mathematically-oriented theoretical and applied topics in information sciences, optimization sciences and related areas since 1980. Subjects include but are not limited to: • Information Sciences • Optimization Sciences • Control Theory • Operational Research • Decision Sciences • Information Theory • Information Technology • Computer Networks and Communications • Mathematical Programming • Modelling and Simulation • Database Management • Applications to Engineering Sciences • Applications to Technology

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Open Access Research Article

Modeling, analyzing and simulating the dynamics of Tuberculosis-Covid-19 co-infection

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* Corresponding author · click or hover a name for details

pp. 73–94Vol. 45Issue 1January 2024DOI: 10.47974/JIOS-1271XML
Received:
15 Feb 2022
Accepted:
05 Jul 2022
Published Online:
29 Jan 2024
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1271
Pages:
73–94

Abstract

Covid-19 and tuberculosis (TB) are two significant infectious illnesses that may pose significant threats to the public health and their co-infection aggravates the issue. Through the use of a set of nonlinear ordinary differential equations and contaminated surfaces from SARS-CoV-2 in the environment, we developed and investigated a mathematical model in this study for the dynamics of the co-infection of Covid-19 and TB transmission. The free equilibrium point of the disease was determined and its stability was investigated. The next generation matrix approach is used to determine the model’s basic reproduction number. The disease-free equilibrium point is not globally asymptotically stable, but it is locally asymptotically stable if R0 < L  We found key model parameters for disease dynamics spread using normalized forward sensitivity analysis. From the numerical simulation results, we conclude that government stakeholders should work in reducing the transmission mechanisms of both diseases. In addition, they should look on mechanisms for removing SARS-CoV-2 contaminated surfaces from the community.

Keywords

Subject Classifications

34D3537C7565L06

References

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