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A simple in-host model for Mycobacterium tuberculosis that captures all infection outcomes

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  • Yimin Du
  • Jianhong Wu
  • Jane M. Heffernan

Abstract

Tuberculosis infection can result in clearance, latent infection, or active disease, with slow or fast progression. A four-dimensional model of in-host tuberculosis infection includes macrophages, T lymphocytes, tuberculosis bacteria, and their interactions. Changes in the infection rate, cell-mediated immunity rate, macrophage loss rate, and bacteria killing rate most affect disease outcomes. Simulations show that a periodic solution can occur. When the infected macrophage killing rate is constant, a backward bifurcation exists and the system is globally stable.

Suggested Citation

  • Yimin Du & Jianhong Wu & Jane M. Heffernan, 2017. "A simple in-host model for Mycobacterium tuberculosis that captures all infection outcomes," Mathematical Population Studies, Taylor & Francis Journals, vol. 24(1), pages 37-63, January.
    • Handle: RePEc:taf:mpopst:v:24:y:2017:i:1:p:37-63
    DOI: 10.1080/08898480.2015.1054220
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    Cited by:

    1. Zhang, Wenjing, 2022. "Disease clearance of tuberculosis infection: An in-host continuous-time Markov chain model," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    2. Ahmed M. Elaiw & Afnan D. Al Agha, 2023. "Analysis of the In-Host Dynamics of Tuberculosis and SARS-CoV-2 Coinfection," Mathematics, MDPI, vol. 11(5), pages 1-24, February.
    3. Ali Algarni & Afnan D. Al Agha & Aisha Fayomi & Hakim Al Garalleh, 2023. "Kinetics of a Reaction-Diffusion Mtb/SARS-CoV-2 Coinfection Model with Immunity," Mathematics, MDPI, vol. 11(7), pages 1-25, April.

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