IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i3p688-d1050469.html
   My bibliography  Save this article

Global Dynamics of an HTLV-I and SARS-CoV-2 Co-Infection Model with Diffusion

Author

Listed:
  • Ahmed M. Elaiw

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

  • Abdulsalam S. Shflot

    (Department of Mathematics, Faculty of Science, King Abdulaziz University, P.O. Box 80203, Jeddah 21589, Saudi Arabia
    Department of Mathematics, Faculty of Science, King Khalid University, P.O. Box 960, Abha 61421, Saudi Arabia)

  • Aatef D. Hobiny

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

  • Shaban A. Aly

    (Department of Mathematics, Faculty of Science, Al-Azhar University, Assiut Branch, Assiut 71524, Egypt)

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel respiratory virus that causes coronavirus disease 2019 (COVID-19). Symptoms of COVID-19 range from mild to severe illness. It was observed that disease progression in COVID-19 patients depends on their immune response, especially in elderly patients whose immune system suppression may put them at increased risk of infection. Human T-cell lymphotropic virus type-I (HTLV-I) attacks the CD4 + T cells (T cells) of the immune system and leads to immune dysfunction. Co-infection with HTLV-I and SARS-CoV-2 has been reported in recent studies. Modeling HTLV-I and SARS-CoV-2 co-infection can be a helpful tool to understand the in-host co-dynamics of these viruses. The aim of this study was to construct a model that characterizes the in-host dynamics of HTLV-I and SARS-CoV-2 co-infection. By considering the mobility of the viruses and cells, the model is represented by a system of partial differential equations (PDEs). The system contains two independent variables, time t and position x, and seven dependent variables for representing the densities of healthy epithelial cells (ECs), latent SARS-CoV-2-infected ECs, active SARS-CoV-2-infected ECs, SARS-CoV-2, healthy T cells, latent HTLV-I-infected T cells and active HTLV-I-infected T cells. We first studied the fundamental properties of the solutions of the system, then deduced all steady states and proved their global properties. We examined the global stability of the steady states by constructing appropriate Lyapunov functions. The analytical results were illustrated by performing numerical simulations. We discussed the effect of HTLV-I infection on COVID-19 progression. The results suggest that patients with HTLV-I have a weakened immune response; consequently, their risk of COVID-19 infection may be increased.

Suggested Citation

  • Ahmed M. Elaiw & Abdulsalam S. Shflot & Aatef D. Hobiny & Shaban A. Aly, 2023. "Global Dynamics of an HTLV-I and SARS-CoV-2 Co-Infection Model with Diffusion," Mathematics, MDPI, vol. 11(3), pages 1-33, January.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:3:p:688-:d:1050469
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/3/688/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/3/688/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Ahmed M. Elaiw & Raghad S. Alsulami & Aatef D. Hobiny, 2022. "Modeling and Stability Analysis of Within-Host IAV/SARS-CoV-2 Coinfection with Antibody Immunity," Mathematics, MDPI, vol. 10(22), pages 1-36, November.
    3. Rehman, Attiq ul & Singh, Ram & Agarwal, Praveen, 2021. "Modeling, analysis and prediction of new variants of covid-19 and dengue co-infection on complex network," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    4. Ahmed M. Elaiw & Abdullah J. Alsaedi & Afnan Diyab Al Agha & Aatef D. Hobiny, 2022. "Global Stability of a Humoral Immunity COVID-19 Model with Logistic Growth and Delays," Mathematics, MDPI, vol. 10(11), pages 1-28, May.
    5. Khajanchi, Subhas & Bera, Sovan & Roy, Tapan Kumar, 2021. "Mathematical analysis of the global dynamics of a HTLV-I infection model, considering the role of cytotoxic T-lymphocytes," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 180(C), pages 354-378.
    6. Omame, Andrew & Abbas, Mujahid & Abdel-Aty, Abdel-Haleem, 2022. "Assessing the impact of SARS-CoV-2 infection on the dynamics of dengue and HIV via fractional derivatives," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    7. Bera, Sovan & Khajanchi, Subhas & Roy, Tapan Kumar, 2022. "Dynamics of an HTLV-I infection model with delayed CTLs immune response," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    8. 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.
    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 & Abdulsalam S. Shflot & Aatef D. Hobiny, 2022. "Global Stability of Delayed SARS-CoV-2 and HTLV-I Coinfection Models within a Host," Mathematics, MDPI, vol. 10(24), pages 1-35, December.
    2. Ahmed M. Elaiw & Raghad S. Alsulami & Aatef D. Hobiny, 2022. "Modeling and Stability Analysis of Within-Host IAV/SARS-CoV-2 Coinfection with Antibody Immunity," Mathematics, MDPI, vol. 10(22), pages 1-36, November.
    3. Han, Lili & Song, Sha & Pan, Qiuhui & He, Mingfeng, 2023. "The impact of multiple population-wide testing and social distancing on the transmission of an infectious disease," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    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. Zhang, Zhenzhen & Ma, Xia & Zhang, Yongxin & Sun, Guiquan & Zhang, Zi-Ke, 2023. "Identifying critical driving factors for human brucellosis in Inner Mongolia, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    6. Ahmed. M. Elaiw & Abdullah J. Alsaedi & Aatef. D. Hobiny & Shaban. A. Aly, 2022. "Global Properties of a Diffusive SARS-CoV-2 Infection Model with Antibody and Cytotoxic T-Lymphocyte Immune Responses," Mathematics, MDPI, vol. 11(1), pages 1-32, December.
    7. Omame, Andrew & Abbas, Mujahid, 2023. "Modeling SARS-CoV-2 and HBV co-dynamics with optimal control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    8. Asamoah, Joshua Kiddy K. & Okyere, Eric & Yankson, Ernest & Opoku, Alex Akwasi & Adom-Konadu, Agnes & Acheampong, Edward & Arthur, Yarhands Dissou, 2022. "Non-fractional and fractional mathematical analysis and simulations for Q fever," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    9. Gharahasanlou, Tohid Kasbi & Roomi, Vahid & Hemmatzadeh, Zeynab, 2022. "Global stability analysis of viral infection model with logistic growth rate, general incidence function and cellular immunity," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 194(C), pages 64-79.
    10. Rehman, Attiq ul & Singh, Ram & Singh, Jagdev, 2022. "Mathematical analysis of multi-compartmental malaria transmission model with reinfection," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).
    11. Li, WenYao & Xue, Xiaoyu & Pan, Liming & Lin, Tao & Wang, Wei, 2022. "Competing spreading dynamics in simplicial complex," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    12. Nie, Yanyi & Zhong, Xiaoni & Lin, Tao & Wang, Wei, 2022. "Homophily in competing behavior spreading among the heterogeneous population with higher-order interactions," Applied Mathematics and Computation, Elsevier, vol. 432(C).
    13. Omame, A. & Abbas, M. & Onyenegecha, C.P., 2021. "A fractional-order model for COVID-19 and tuberculosis co-infection using Atangana–Baleanu derivative," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    14. 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.
    15. Zhang, Tongqian & Xu, Xinna & Wang, Xinzeng, 2023. "Dynamic analysis of a cytokine-enhanced viral infection model with time delays and CTL immune response," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    16. Bera, Sovan & Khajanchi, Subhas & Roy, Tapan Kumar, 2022. "Dynamics of an HTLV-I infection model with delayed CTLs immune response," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    17. Elaiw, A.M. & Alsaedi, A.J. & Hobiny, A.D. & Aly, S., 2023. "Stability of a delayed SARS-CoV-2 reactivation model with logistic growth and adaptive immune response," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 616(C).
    18. Alfifi, H.Y., 2023. "Effects of diffusion and delayed immune response on dynamic behavior in a viral model," Applied Mathematics and Computation, Elsevier, vol. 441(C).
    19. Xinggui Li & Xinsong Yang, 2023. "Global Stabilization of Delayed Feedback Financial System Involved in Advertisement under Impulsive Disturbance," Mathematics, MDPI, vol. 11(9), pages 1-12, April.
    20. Miaadi, Foued & Li, Xiaodi, 2021. "Impulsive effect on fixed-time control for distributed delay uncertain static neural networks with leakage delay," Chaos, Solitons & Fractals, Elsevier, vol. 142(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:688-:d:1050469. 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.