IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i16p3485-d1215668.html
   My bibliography  Save this article

Modeling the Within-Host Dynamics of SARS-CoV-2 Infection Based on Antiviral Treatment

Author

Listed:
  • Tianqi Song

    (School of Economics and Management, Shanghai Maritime University, Shanghai 201306, China)

  • Yishi Wang

    (Shanghai Institute of Aerospace System Engineering, Shanghai 201100, China)

  • Xi Gu

    (School of Economics and Management, Shanghai Maritime University, Shanghai 201306, China)

  • Sijia Qiao

    (Department of Finance, Shanghai National Accounting Institute, Shanghai 201702, China)

Abstract

The COVID-19 pandemic has highlighted the profound impact of the SARS-CoV-2 virus as a significant threat to human health. There is an urgent need to develop a comprehensive understanding of the current outbreak by studying the dynamics of the virus within the human body. In this research, we present a mathematical model that explores the progression of SARS-CoV-2 infection, taking into account both the innate and adaptive immune responses. We calculated the basic reproduction number and analyzed the stability of the equilibria. Additionally, we demonstrated the existence of a periodic solution through numerical simulations. By conducting a global sensitivity analysis, we determined the significance of the model parameters and investigated the influence of key parameters on viral load. The results emphasized the crucial roles of cytokines and antibodies in shaping the dynamics of SARS-CoV-2. Furthermore, we evaluated the effectiveness of antiviral treatment in controlling the dynamics of SARS-CoV-2 infection. Our findings revealed a direct relationship between the basic reproduction number and the impact of antiviral treatment. To evaluate the effect of antiviral treatment on viral load, we conducted numerical simulations.

Suggested Citation

  • Tianqi Song & Yishi Wang & Xi Gu & Sijia Qiao, 2023. "Modeling the Within-Host Dynamics of SARS-CoV-2 Infection Based on Antiviral Treatment," Mathematics, MDPI, vol. 11(16), pages 1-19, August.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:16:p:3485-:d:1215668
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/16/3485/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/16/3485/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Julian Braun & Lucie Loyal & Marco Frentsch & Daniel Wendisch & Philipp Georg & Florian Kurth & Stefan Hippenstiel & Manuela Dingeldey & Beate Kruse & Florent Fauchere & Emre Baysal & Maike Mangold & , 2020. "SARS-CoV-2-reactive T cells in healthy donors and patients with COVID-19," Nature, Nature, vol. 587(7833), pages 270-274, November.
    2. Farooq, Junaid & Bazaz, Mohammad Abid, 2020. "A novel adaptive deep learning model of Covid-19 with focus on mortality reduction strategies," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    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. Meng Wang & Adeline Dehlinger & Camila Fernández Zapata & Maya Golan & Gerardina Gallaccio & Leif E. Sander & Stephan Schlickeiser & Desiree Kunkel & Tanja Schmitz-Hübsch & Birgit Sawitzki & Arnon Kar, 2023. "Associations of myeloid cells with cellular and humoral responses following vaccinations in patients with neuroimmunological diseases," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Jonas S. Heitmann & Claudia Tandler & Maddalena Marconato & Annika Nelde & Timorshah Habibzada & Susanne M. Rittig & Christian M. Tegeler & Yacine Maringer & Simon U. Jaeger & Monika Denk & Marion Ric, 2023. "Phase I/II trial of a peptide-based COVID-19 T-cell activator in patients with B-cell deficiency," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    3. Fehaid Salem Alshammari & Fahir Talay Akyildiz, 2023. "Epidemic Waves in a Stochastic SIRVI Epidemic Model Incorporating the Ornstein–Uhlenbeck Process," Mathematics, MDPI, vol. 11(18), pages 1-15, September.
    4. Rasheed, Jawad & Jamil, Akhtar & Hameed, Alaa Ali & Aftab, Usman & Aftab, Javaria & Shah, Syed Attique & Draheim, Dirk, 2020. "A survey on artificial intelligence approaches in supporting frontline workers and decision makers for the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    5. Jelena Musulin & Sandi Baressi Šegota & Daniel Štifanić & Ivan Lorencin & Nikola Anđelić & Tijana Šušteršič & Anđela Blagojević & Nenad Filipović & Tomislav Ćabov & Elitza Markova-Car, 2021. "Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review," IJERPH, MDPI, vol. 18(8), pages 1-39, April.
    6. Salim S Abdool Karim & Segenet Kelemu & Cheryl Baxter, 2021. "COVID-19 in Africa: Catalyzing change for sustainable development," PLOS Medicine, Public Library of Science, vol. 18(11), pages 1-4, November.
    7. Magen E. Francis & Ethan B. Jansen & Anthony Yourkowski & Alaa Selim & Cynthia L. Swan & Brian K. MacPhee & Brittany Thivierge & Rachelle Buchanan & Kerry J. Lavender & Joseph Darbellay & Matthew B. R, 2023. "Previous infection with seasonal coronaviruses does not protect male Syrian hamsters from challenge with SARS-CoV-2," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    8. Dhiraj Mannar & James W. Saville & Chad Poloni & Xing Zhu & Alison Bezeruk & Keith Tidey & Sana Ahmed & Katharine S. Tuttle & Faezeh Vahdatihassani & Spencer Cholak & Laura Cook & Theodore S. Steiner , 2024. "Altered receptor binding, antibody evasion and retention of T cell recognition by the SARS-CoV-2 XBB.1.5 spike protein," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    9. Deanna M. Santer & Daniel Li & Yanal Ghosheh & Muhammad Atif Zahoor & Dhanvi Prajapati & Bettina E. Hansen & D. Lorne J. Tyrrell & Jordan J. Feld & Adam J. Gehring, 2022. "Interferon-λ treatment accelerates SARS-CoV-2 clearance despite age-related delays in the induction of T cell immunity," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    10. Iris N. Pardieck & Tetje C. van der Sluis & Esmé T. I. van der Gracht & Dominique M. B. Veerkamp & Felix M. Behr & Suzanne van Duikeren & Guillaume Beyrend & Jasper Rip & Reza Nadafi & Elham Beyranvan, 2022. "A third vaccination with a single T cell epitope confers protection in a murine model of SARS-CoV-2 infection," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    11. Tabea M. Eser & Olga Baranov & Manuel Huth & Mohammed I. M. Ahmed & Flora Deák & Kathrin Held & Luming Lin & Kami Pekayvaz & Alexander Leunig & Leo Nicolai & Georgios Pollakis & Marcus Buggert & David, 2023. "Nucleocapsid-specific T cell responses associate with control of SARS-CoV-2 in the upper airways before seroconversion," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    12. Thomas Wieland, 2020. "Flatten the Curve! Modeling SARS-CoV-2/COVID-19 Growth in Germany at the County Level," REGION, European Regional Science Association, vol. 7, pages 43-83.
    13. Rúbens Prince dos Santos Alves & Julia Timis & Robyn Miller & Kristen Valentine & Paolla Beatriz Almeida Pinto & Andrew Gonzalez & Jose Angel Regla-Nava & Erin Maule & Michael N. Nguyen & Norazizah Sh, 2024. "Human coronavirus OC43-elicited CD4+ T cells protect against SARS-CoV-2 in HLA transgenic mice," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    14. Atienza-Diez, Iker & Seoane, Luís F., 2023. "Long- and short-term effects of cross-immunity in epidemic dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    15. Daan K. J. Pieren & Sebastián G. Kuguel & Joel Rosado & Alba G. Robles & Joan Rey-Cano & Cristina Mancebo & Juliana Esperalba & Vicenç Falcó & María J. Buzón & Meritxell Genescà, 2023. "Limited induction of polyfunctional lung-resident memory T cells against SARS-CoV-2 by mRNA vaccination compared to infection," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    16. Julia T. Castro & Patrick Azevedo & Marcílio J. Fumagalli & Natalia S. Hojo-Souza & Natalia Salazar & Gregório G. Almeida & Livia I. Oliveira & Lídia Faustino & Lis R. Antonelli & Tomas G. Marçal & Ma, 2022. "Promotion of neutralizing antibody-independent immunity to wild-type and SARS-CoV-2 variants of concern using an RBD-Nucleocapsid fusion protein," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    17. Eva-Maria Jacobsen & Dorit Fabricius & Magdalena Class & Fernando Topfstedt & Raquel Lorenzetti & Iga Janowska & Franziska Schmidt & Julian Staniek & Maria Zernickel & Thomas Stamminger & Andrea N. Di, 2022. "High antibody levels and reduced cellular response in children up to one year after SARS-CoV-2 infection," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    18. Tayarani N., Mohammad-H., 2021. "Applications of artificial intelligence in battling against covid-19: A literature review," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    19. Aloysious Ssemaganda & Huong Mai Nguyen & Faisal Nuhu & Naima Jahan & Catherine M. Card & Sandra Kiazyk & Giulia Severini & Yoav Keynan & Ruey-Chyi Su & Hezhao Ji & Bernard Abrenica & Paul J. McLaren , 2022. "Expansion of cytotoxic tissue-resident CD8+ T cells and CCR6+CD161+ CD4+ T cells in the nasal mucosa following mRNA COVID-19 vaccination," Nature Communications, Nature, vol. 13(1), pages 1-9, December.

    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:16:p:3485-:d:1215668. 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.