An age-structured tuberculosis model with information and immigration: Stability and simulation study

Author:

Liu Lili1ORCID,Zhang Jian1,Li Yazhi2,Ren Xinzhi3

Affiliation:

1. Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention, Complex Systems Research Center, Shanxi University, Taiyuan 030006, P. R. China

2. Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province, School of Mathematics and Statistics, Qiannan Normal University for Nationalities, Duyun 558000, P. R. China

3. School of Mathematics and Statistics, Southwest University, Chongqing 400715, P. R. China

Abstract

This paper establishes an age-structured Tuberculosis (TB) model to investigate the joint impacts of information and immigration of population on the spread of TB disease. Mathematically, we show that the model is point dissipative, and the semi-flow generated by the model has the property of asymptotic smoothness, and then study the existence and global stability of positive steady state by the direct Lyapunov functional. Numerically, by using Matlab software, we verify the theoretical results, and further explore the influence of information (including information coverage and disease-related memory delay) and immigration on the final size of TB disease. The simulation results show that both information coverage and immigration are positive correlated with the final size of disease, and disease-related memory delay can affect the arrival time of positive steady state, which implies us that improving information coverage, enlarging disease-related memory, and reducing the immigration of population (especially latent and infected individuals) can effectively control the progression of TB disease.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shanxi Province

the Natural Science Foundation of Guizhou Province

the Project funded by China Postdoctoral Science Foundation

Publisher

World Scientific Pub Co Pte Ltd

Subject

Applied Mathematics,Modeling and Simulation

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