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Kinetics of a Reaction-Diffusion Mtb/SARS-CoV-2 Coinfection Model with Immunity

Author

Listed:
  • Ali Algarni

    (Department of Statistics, Faculty of Science, King Abdulaziz University, P.O. Box 80203, Jeddah 21589, Saudi Arabia)

  • Afnan D. Al Agha

    (Department of Mathematical Science, College of Engineering, University of Business and Technology, P.O. Box 110200, Jeddah 21361, Saudi Arabia)

  • Aisha Fayomi

    (Department of Statistics, Faculty of Science, King Abdulaziz University, P.O. Box 80203, Jeddah 21589, Saudi Arabia)

  • Hakim Al Garalleh

    (Department of Mathematical Science, College of Engineering, University of Business and Technology, P.O. Box 110200, Jeddah 21361, Saudi Arabia)

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Mycobacterium tuberculosis (Mtb) coinfection has been observed in a number of nations and it is connected with severe illness and death. The paper studies a reaction–diffusion within-host Mtb/SARS-CoV-2 coinfection model with immunity. This model explores the connections between uninfected epithelial cells, latently Mtb-infected epithelial cells, productively Mtb-infected epithelial cells, SARS-CoV-2-infected epithelial cells, free Mtb particles, free SARS-CoV-2 virions, and CTLs. The basic properties of the model’s solutions are verified. All equilibrium points with the essential conditions for their existence are calculated. The global stability of these equilibria is established by adopting compatible Lyapunov functionals. The theoretical outcomes are enhanced by implementing numerical simulations. It is found that the equilibrium points mirror the single infection and coinfection states of SARS-CoV-2 with Mtb. The threshold conditions that determine the movement from the monoinfection to the coinfection state need to be tested when developing new treatments for coinfected patients. The impact of the diffusion coefficients should be monitored at the beginning of coinfection as it affects the initial distribution of particles in space.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:7:p:1715-:d:1115024
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    References listed on IDEAS

    as
    1. 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.
    2. Bandekar, Shraddha Ramdas & Ghosh, Mini, 2022. "A co-infection model on TB - COVID-19 with optimal control and sensitivity analysis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 200(C), pages 1-31.
    3. Ahmed M. Elaiw & Afnan D. Al Agha, 2022. "Global Stability of a Reaction–Diffusion Malaria/COVID-19 Coinfection Dynamics Model," Mathematics, MDPI, vol. 10(22), pages 1-31, November.
    4. Kassahun Getnet Mekonen & Shiferaw Feyissa Balcha & Legesse Lemecha Obsu & Abdulkadir Hassen, 2022. "Mathematical Modeling and Analysis of TB and COVID-19 Coinfection," Journal of Applied Mathematics, Hindawi, vol. 2022, pages 1-20, March.
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