Modeling the influence of fear and patients’ attitudes on the transmission dynamics of tuberculosis

Chiganga S. Ruoja, Maranya Mayengo, Nkuba Nyerere, Farai Nyabadza

Research output: Contribution to journalArticlepeer-review

Abstract

In this study we discussed the ongoing global health challenge of tuberculosis (TB), which is caused by the Mycobacterium tuberculosis bacteria. While in several studies, the transmission dynamics of TB were examined, it is noted in this work that the impacts of social processes like disease-induced fear and patient attitudes toward hospital treatment have been receiving a poor discussion on understanding the disease transmission and its control. In this paper we present and discuss a deterministic mathematical model to investigate how these social processes influence the transmission dynamics of TB. The basic reproduction number R0 is calculated and used to examine the stability of steady states. Additionally, we conducted a sensitivity analysis which tells what are the parameters that most significantly affect R0. The key findings from the analytical and numerical simulations indicate that high levels of disease-induced fear in the population, coupled with positive attitudes toward hospital treatment, can significantly reduce TB prevalence. Based on these results, the study recommends implementing control programs that address these social processes as part of the ongoing efforts to combat the TB burden.

Original languageEnglish
Article number67
JournalModeling Earth Systems and Environment
Volume11
Issue number1
DOIs
Publication statusPublished - Feb 2025

Keywords

  • Basic reproduction number
  • Fear
  • Mathematical model
  • Patients’ attitudes
  • Simulation
  • Tuberculosis

ASJC Scopus subject areas

  • General Environmental Science
  • General Agricultural and Biological Sciences
  • Computers in Earth Sciences
  • Statistics, Probability and Uncertainty

Fingerprint

Dive into the research topics of 'Modeling the influence of fear and patients’ attitudes on the transmission dynamics of tuberculosis'. Together they form a unique fingerprint.

Cite this