Modelling the preventive treatment under media impact on tuberculosis: A comparison in four regions of China

Jun Zhang; Yasuhiro Takeuchi; Yueping Dong; Zhihang Peng

doi:10.1016/j.idm.2024.02.006

Modelling the preventive treatment under media impact on tuberculosis: A comparison in four regions of China

Infect Dis Model. 2024 Feb 12;9(2):483-500. doi: 10.1016/j.idm.2024.02.006. eCollection 2024 Jun.

Authors

Jun Zhang¹, Yasuhiro Takeuchi², Yueping Dong¹, Zhihang Peng³

Affiliations

¹ School of Mathematics and Statistics, and Key Laboratory of Nonlinear Analysis & Applications (Ministry of Education), Central China Normal University, Wuhan, 430079, China.
² College of Science and Engineering, Aoyama Gakuin University, Kanagawa, 252-5258, Japan.
³ National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.

Abstract

Preventive treatment for people with latent Tuberculosis infection (LTBI) has aroused our great interest. In this paper, we propose and analyze a novel mathematical model of TB considering preventive treatment with media impact. The basic reproduction number $R_{0}$ is defined by the next generation matrix method. In the case without media impact, we prove that the disease-free equilibrium is globally asymptotically stable (unstable) if $R_{0} < 1$ $(R_{0} > 1)$ . Furthermore, we obtain that a unique endemic equilibrium exists when $R_{0} > 1$ , which is globally asymptotically stable in the case of permanent immunity and no media impact. We fit the model to the newly reported TB cases data from 2009 to 2019 of four regions in China and estimate the parameters. And we estimated $R_{0} = 0.5013 < 1$ in Hubei indicating that TB in Hubei will be eliminated in the future. However, the estimated $R_{0} = 1.015 > 1$ in Henan, $R_{0} = 1.282 > 1$ in Jiangxi and $R_{0} = 1.930 > 1$ in Xinjiang imply that TB will continue to persist in these three regions without further prevention and control measures. Besides, sensitivity analysis is carried out to illustrate the role of model parameters for TB control. Our finding reveals that appropriately improving the rate of timely treatment for actively infected people and increasing the rate of individuals with LTBI seeking preventive treatment could achieve the goal of TB elimination. In addition, another interesting finding shows that media impact can only reduce the number of active infections to a limited extent, but cannot change the prevalence of TB.

Keywords: Latent tuberculosis infection; Mathematical model; Media impact; Preventive treatment; Tuberculosis elimination.