Global Dynamics of an Age-Structured Tuberculosis Model with Vaccine Failure and Nonlinear Infection Force

Author:

Guo Zhongkai1,Zhang Liang2

Affiliation:

1. School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China

2. College of Science, Northwest A&F University, Yangling 712100, China

Abstract

China bears a heavy burden due to tuberculosis (TB) with hundreds of thousands of people falling ill with the disease every year. Therefore, it is necessary to understand the effectiveness of current control measures in China. In this paper, we first present a TB model that incorporates both vaccination and treatment. Additionally, the model considers TB transmission characteristics such as relapse and variable latency. We then define the basic reproduction number R0 of the proposed model and indicate that the disease-free equilibrium state is globally asymptotically stable if R0<1, and the endemic equilibrium state is globally asymptotically stable if R0>1. We then apply the Grey Wolf Optimizer algorithm to obtain the parameters and initial values of the model by combining TB data collected in China from 2007 to 2020. Through the partial rank correlation coefficient method, we identify the parameters that are most sensitive to R0. Based on the analysis results of the model, we propose some suggestions for TB control measures in the conclusion section.

Funder

Natural Science Foundation of Gansu of China

Publisher

MDPI AG

Subject

Geometry and Topology,Logic,Mathematical Physics,Algebra and Number Theory,Analysis

Reference41 articles.

1. WHO (2023, April 05). Global Tuberculosis Report 2022, Available online: https://www.who.int/publications/i/item/9789240061729.

2. Analysis of an age-structured tuberculosis model with treatment and relapse;Guo;J. Math. Biol.,2021

3. Transmission dynamics of tuberculosis with multiple re-infections;Das;Chaos Solitons Fractals,2020

4. Optimal intervention strategy for prevention tuberculosis using a smoking-tuberculosis model;Choi;J. Theor. Biol.,2015

5. The dynamics of a stochastic vaccinated tuberculosis model with treatment;Liu;Phys. A Stat. Mech. Appl.,2019

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