IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i3p592-d1044456.html
   My bibliography  Save this article

Effect of Macrophages and Latent Reservoirs on the Dynamics of HTLV-I and HIV-1 Coinfection

Author

Listed:
  • A. M. Elaiw

    (Department of Mathematics, Faculty of Science, King Abdulaziz University, P.O. Box 80203, Jeddah 21589, Saudi Arabia
    Department of Mathematics, Faculty of Science, Al-Azhar University, Assiut Branch, Assiut 71511, Egypt)

  • N. H. AlShamrani

    (Department of Mathematics, Faculty of Science, University of Jeddah, P.O. Box 80327, Jeddah 21589, Saudi Arabia)

  • E. Dahy

    (Department of Mathematics, Faculty of Science, Al-Azhar University, Assiut Branch, Assiut 71511, Egypt)

  • A. A. Abdellatif

    (Department of Mathematics, Faculty of Science, Al-Azhar University, Assiut Branch, Assiut 71511, Egypt)

  • Aeshah A. Raezah

    (Department of Mathematics, Faculty of Science, King Khalid University, Abha 62529, Saudi Arabia)

Abstract

Human immunodeficiency virus type 1 (HIV-1) and human T-lymphotropic virus type I (HTLV-I) are two retroviruses that have a similar fashion of transmission via sharp objects contaminated by viruses, transplant surgery, transfusion, and sexual relations. Simultaneous infections with HTLV-I and HIV-1 usually occur in areas where both viruses have become endemic. CD 4 + T cells are the main targets of HTLV-I, while HIV-1 can infect CD 4 + T cells and macrophages. It is the aim of this study to develop a model of HTLV-I and HIV-1 coinfection that describes the interactions of nine compartments: susceptible cells of both CD 4 + T cells and macrophages, HIV-1-infected cells that are latent/active in both CD 4 + T cells and macrophages, HTLV-I-infected CD 4 + T cells that are latent/active, and free HIV-1 particles. The well-posedness, existence of equilibria, and global stability analysis of our model are investigated. The Lyapunov function and LaSalle’s invariance principle were used to study the global asymptotic stability of all equilibria. The theoretically predicted outcomes were verified by utilizing numerical simulations. The effect of including the macrophages and latent reservoirs in the HTLV-I and HIV-1 coinfection model is discussed. We show that the presence of macrophages makes a coinfection model more realistic when the case of the coexistence of HIV-1 and HTLV-I is established. Moreover, we have shown that neglecting the latent reservoirs in HTLV-I and HIV-1 coinfection modeling will lead to the design of an overflow of anti-HIV-1 drugs.

Suggested Citation

  • A. M. Elaiw & N. H. AlShamrani & E. Dahy & A. A. Abdellatif & Aeshah A. Raezah, 2023. "Effect of Macrophages and Latent Reservoirs on the Dynamics of HTLV-I and HIV-1 Coinfection," Mathematics, MDPI, vol. 11(3), pages 1-26, January.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:3:p:592-:d:1044456
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/3/592/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/3/592/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. A. M. Elaiw, 2012. "Global Dynamics of an HIV Infection Model with Two Classes of Target Cells and Distributed Delays," Discrete Dynamics in Nature and Society, Hindawi, vol. 2012, pages 1-13, August.
    2. Feng, Tao & Qiu, Zhipeng & Meng, Xinzhu & Rong, Libin, 2019. "Analysis of a stochastic HIV-1 infection model with degenerate diffusion," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 437-455.
    3. Qi, Kai & Jiang, Daqing & Hayat, Tasawar & Alsaedi, Ahmed, 2021. "Virus dynamic behavior of a stochastic HIV/AIDS infection model including two kinds of target cell infections and CTL immune responses," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 548-570.
    4. Wang, Yan & Liu, Xianning, 2017. "Stability and Hopf bifurcation of a within-host chikungunya virus infection model with two delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 138(C), pages 31-48.
    5. Alan S. Perelson & Paulina Essunger & Yunzhen Cao & Mika Vesanen & Arlene Hurley & Kalle Saksela & Martin Markowitz & David D. Ho, 1997. "Decay characteristics of HIV-1-infected compartments during combination therapy," Nature, Nature, vol. 387(6629), pages 188-191, May.
    6. A. M. Elaiw & E. Kh. Elnahary, 2019. "Analysis of General Humoral Immunity HIV Dynamics Model with HAART and Distributed Delays," Mathematics, MDPI, vol. 7(2), pages 1-35, February.
    7. Konstantin E. Starkov & Anatoly N. Kanatnikov, 2021. "Eradication Conditions of Infected Cell Populations in the 7-Order HIV Model with Viral Mutations and Related Results," Mathematics, MDPI, vol. 9(16), pages 1-14, August.
    8. Alan S. Perelson & Avidan U. Neumann & Martin Markowitz & John M. Leonard & David D. Ho, 1996. "HIV-1 Dynamics In Vivo: Virion Clearance Rate, Infected Cell Lifespan, and Viral Generation Time," Working Papers 96-02-004, Santa Fe Institute.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ahmed M. Elaiw & Safiya F. Alshehaiween & Aatef D. Hobiny, 2019. "Global Properties of a Delay-Distributed HIV Dynamics Model Including Impairment of B-Cell Functions," Mathematics, MDPI, vol. 7(9), pages 1-27, September.
    2. A. M. Elaiw & E. Kh. Elnahary, 2019. "Analysis of General Humoral Immunity HIV Dynamics Model with HAART and Distributed Delays," Mathematics, MDPI, vol. 7(2), pages 1-35, February.
    3. Ahmed M. Elaiw & Taofeek O. Alade & Saud M. Alsulami, 2018. "Global Stability of Within-Host Virus Dynamics Models with Multitarget Cells," Mathematics, MDPI, vol. 6(7), pages 1-19, July.
    4. Ahmed M. Elaiw & Aeshah A. Raezah & Matuka A. Alshaikh, 2023. "Global Dynamics of Viral Infection with Two Distinct Populations of Antibodies," Mathematics, MDPI, vol. 11(14), pages 1-26, July.
    5. Prakash, M. & Rakkiyappan, R. & Manivannan, A. & Cao, Jinde, 2019. "Dynamical analysis of antigen-driven T-cell infection model with multiple delays," Applied Mathematics and Computation, Elsevier, vol. 354(C), pages 266-281.
    6. Tao Lu & Yangxin Huang & Min Wang & Feng Qian, 2014. "A refined parameter estimating approach for HIV dynamic model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(8), pages 1645-1657, August.
    7. Attaullah, & Jan, Rashid & Yüzbaşı, Şuayip, 2021. "Dynamical behaviour of HIV Infection with the influence of variable source term through Galerkin method," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    8. Chen, Wei & Zhang, Long & Wang, Ning & Teng, Zhidong, 2024. "Bifurcation analysis and chaos for a double-strains HIV coinfection model with intracellular delays, saturated incidence and Logistic growth," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 223(C), pages 617-641.
    9. González, Ramón E.R. & Coutinho, Sérgio & Zorzenon dos Santos, Rita Maria & de Figueirêdo, Pedro Hugo, 2013. "Dynamics of the HIV infection under antiretroviral therapy: A cellular automata approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4701-4716.
    10. Christian L Althaus & Beda Joos & Alan S Perelson & Huldrych F Günthard, 2014. "Quantifying the Turnover of Transcriptional Subclasses of HIV-1-Infected Cells," PLOS Computational Biology, Public Library of Science, vol. 10(10), pages 1-11, October.
    11. Elaiw, Ahmed M. & Alshaikh, Matuka A., 2020. "Global stability of discrete pathogen infection model with humoral immunity and cell-to-cell transmission," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    12. Arshad, Sadia & Defterli, Ozlem & Baleanu, Dumitru, 2020. "A second order accurate approximation for fractional derivatives with singular and non-singular kernel applied to a HIV model," Applied Mathematics and Computation, Elsevier, vol. 374(C).
    13. Qi, Haokun & Meng, Xinzhu, 2021. "Mathematical modeling, analysis and numerical simulation of HIV: The influence of stochastic environmental fluctuations on dynamics," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 187(C), pages 700-719.
    14. Sutimin, & Wijaya, Karunia Putra & Páez Chávez, Joseph & Tian, Tianhai, 2021. "An in-host HIV-1 infection model incorporating quiescent and activated CD4+ T cells as well as CTL response," Applied Mathematics and Computation, Elsevier, vol. 409(C).
    15. Abraham J. Arenas & Gilberto González-Parra & Jhon J. Naranjo & Myladis Cogollo & Nicolás De La Espriella, 2021. "Mathematical Analysis and Numerical Solution of a Model of HIV with a Discrete Time Delay," Mathematics, MDPI, vol. 9(3), pages 1-21, January.
    16. Qi, Kai & Jiang, Daqing & Hayat, Tasawar & Alsaedi, Ahmed, 2021. "Virus dynamic behavior of a stochastic HIV/AIDS infection model including two kinds of target cell infections and CTL immune responses," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 548-570.
    17. Iraj Hosseini & Feilim Mac Gabhann, 2012. "Multi-Scale Modeling of HIV Infection in vitro and APOBEC3G-Based Anti-Retroviral Therapy," PLOS Computational Biology, Public Library of Science, vol. 8(2), pages 1-17, February.
    18. E Fabian Cardozo & Adriana Andrade & John W Mellors & Daniel R Kuritzkes & Alan S Perelson & Ruy M Ribeiro, 2017. "Treatment with integrase inhibitor suggests a new interpretation of HIV RNA decay curves that reveals a subset of cells with slow integration," PLOS Pathogens, Public Library of Science, vol. 13(7), pages 1-18, July.
    19. Nicola Bellomo & Richard Bingham & Mark A.J. Chaplain & Giovanni Dosi & Guido Forni & Damian A. Knopoff & John Lowengrub & Reidun Twarock & Maria Enrica Virgillito, 2020. "A multi-scale model of virus pandemic: Heterogeneous interactive entities in a globally connected world," LEM Papers Series 2020/16, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    20. Sun, Hongquan & Li, Jin, 2020. "A numerical method for a diffusive virus model with general incidence function, cell-to-cell transmission and time delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:3:p:592-:d:1044456. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.