IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v397y2021ics0096300320308791.html
   My bibliography  Save this article

Significance of antiviral therapy and CTL-mediated immune response in containing hepatitis B and C virus infection

Author

Listed:
  • Njagarah, John B.H.
  • Nyabadza, Farai
  • Kgosimore, Moatlhodi
  • Hui, Cang

Abstract

Viral infections remain a major cause of deaths globally. Here, we focus on Hepatitis B and C viruses (HBV and HCV) infection dynamics in the liver and blood cells, taking into account non-cytotoxic and cytotoxic mediated immune response as well as antiviral therapy. The analysis of the model is presented in terms of the reproduction number, R0. The system has a globally stable disease-free equilibrium when R0 is below unit. It exhibits forward bifurcation when R0 is greater than one, with a locally asymptotically stable endemic equilibrium point. By carrying out sensitivity analysis using the Latin Hypercube Sampling scheme (LHS), we determine the key processes that are essential in containing the infection. Our results suggest that, the production of virions from blood and liver cells as well as degeneration of Cytotoxic T-Lymphocytes (CTLs) can greatly aggravate HBV and HCV infections. Moreover, CTL-mediated immune response alone cannot effectively contain the infection. Although virion production from the liver and blood as well as per-capita loss of CTLs were observed to greatly aggravate the infection, their effects imposed on the infection dynamics were not significantly different. We recommend based on the results that, use of highly effective antiviral/combination therapy to block production of new virions is an ideal approach to containing the infections.

Suggested Citation

  • Njagarah, John B.H. & Nyabadza, Farai & Kgosimore, Moatlhodi & Hui, Cang, 2021. "Significance of antiviral therapy and CTL-mediated immune response in containing hepatitis B and C virus infection," Applied Mathematics and Computation, Elsevier, vol. 397(C).
    • Handle: RePEc:eee:apmaco:v:397:y:2021:i:c:s0096300320308791
    DOI: 10.1016/j.amc.2020.125926
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300320308791
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2020.125926?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kassa, Semu M. & Njagarah, John B.H. & Terefe, Yibeltal A., 2020. "Analysis of the mitigation strategies for COVID-19: From mathematical modelling perspective," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang, Xue & Su, Yongmei & Zhuo, Xinjian & Gao, Tianhong, 2023. "Global analysis for a delayed HCV model with saturation incidence and two target cells," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).

    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. Asamoah, Joshua Kiddy K. & Owusu, Mark A. & Jin, Zhen & Oduro, F. T. & Abidemi, Afeez & Gyasi, Esther Opoku, 2020. "Global stability and cost-effectiveness analysis of COVID-19 considering the impact of the environment: using data from Ghana," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    2. Bedilu Alamirie Ejigu & Manalebish Debalike Asfaw & Lisa Cavalerie & Tilahun Abebaw & Mark Nanyingi & Matthew Baylis, 2021. "Assessing the impact of non-pharmaceutical interventions (NPI) on the dynamics of COVID-19: A mathematical modelling study of the case of Ethiopia," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-21, November.
    3. Ndenda, J.P. & Njagarah, J.B.H. & Shaw, S., 2021. "Role of immunotherapy in tumor-immune interaction: Perspectives from fractional-order modelling and sensitivity analysis," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    4. Daisuke Fujii & Taisuke Nakata & Takeshi Ojima, 2022. "Heterogeneous Risk Attitudes and Waves of Infection," CARF F-Series CARF-F-546, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    5. Djaoue, Seraphin & Guilsou Kolaye, Gabriel & Abboubakar, Hamadjam & Abba Ari, Ado Adamou & Damakoa, Irepran, 2020. "Mathematical modeling, analysis and numerical simulation of the COVID-19 transmission with mitigation of control strategies used in Cameroon," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    6. Khatun, Mst Sebi & Das, Samhita & Das, Pritha, 2023. "Dynamics and control of an SITR COVID-19 model with awareness and hospital bed dependency," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    7. Koutou, Ousmane & Diabaté, Abou Bakari & Sangaré, Boureima, 2023. "Mathematical analysis of the impact of the media coverage in mitigating the outbreak of COVID-19," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 205(C), pages 600-618.
    8. Sara K Al-Harbi & Salma M Al-Tuwairqi, 2022. "Modeling the effect of lockdown and social distancing on the spread of COVID-19 in Saudi Arabia," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-40, April.
    9. Mishra, Bimal Kumar & Keshri, Ajit Kumar & Saini, Dinesh Kumar & Ayesha, Syeda & Mishra, Binay Kumar & Rao, Yerra Shankar, 2021. "Mathematical model, forecast and analysis on the spread of COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    10. Prem Kumar, R. & Santra, P.K. & Mahapatra, G.S., 2023. "Global stability and analysing the sensitivity of parameters of a multiple-susceptible population model of SARS-CoV-2 emphasising vaccination drive," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 741-766.
    11. Caraballo, T. & Settati, A. & Lahrouz, A. & Boutouil, S. & Harchaoui, B., 2024. "On the stochastic threshold of the COVID-19 epidemic model incorporating jump perturbations," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    12. Çaparoğlu, Ömer Faruk & Ok, Yeşim & Tutam, Mahmut, 2021. "To restrict or not to restrict? Use of artificial neural network to evaluate the effectiveness of mitigation policies: A case study of Turkey," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    13. Toshikazu Kuniya, 2021. "Structure of epidemic models: toward further applications in economics," The Japanese Economic Review, Springer, vol. 72(4), pages 581-607, October.
    14. Terefe, Y.A. & Njagarah, J.B.H. & Kassa, S.M., 2023. "Effect of cross-border migration on the healthcare system of a destination community: Insights from mathematical modelling of COVID-19 in a developing country," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 208(C), pages 444-479.
    15. Barbosa, Charles H.X.B. & Dias, Claudia M. & Pastore, Dayse H. & Silva, José C.R. & Costa, Anna R.C. & Santos, Isaac P. & Azevedo, Ramoni Z.S. & Figueira, Raquel M.A. & Fortunato, Humberto F.M., 2023. "Analysis of a mathematical model for golden mussels infestation," Ecological Modelling, Elsevier, vol. 486(C).
    16. Huda Abdul Satar & Raid Kamel Naji, 2023. "A Mathematical Study for the Transmission of Coronavirus Disease," Mathematics, MDPI, vol. 11(10), pages 1-20, May.
    17. Pitchaimani, M. & Brasanna Devi, M., 2021. "Stochastic probical strategies in a delay virus infection model to combat COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    18. Miraj Ahmed Bhuiyan & Tiziana Crovella & Annarita Paiano & Helena Alves, 2021. "A Review of Research on Tourism Industry, Economic Crisis and Mitigation Process of the Loss: Analysis on Pre, During and Post Pandemic Situation," Sustainability, MDPI, vol. 13(18), pages 1-27, September.
    19. Vashishth, Anil K. & Basaiti, Komal, 2024. "Modeling the effect of non-pharmaceutical measures and vaccination on the spread of two variants of COVID-19 in India," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 217(C), pages 139-168.

    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:eee:apmaco:v:397:y:2021:i:c:s0096300320308791. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.