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Computer Research and Modeling, 2022, Volume 14, Issue 3, Pages 619–645
DOI: https://doi.org/10.20537/2076-7633-2022-14-3-619-645
(Mi crm987)
 

This article is cited in 2 scientific papers (total in 2 papers)

ANALYSIS AND MODELING OF COMPLEX LIVING SYSTEMS

Modelling of cytokine storm in respiratory viral infections

M. Leonabc, A. A. Tokarevad, V. A. Vol'pertaef

a Peoples Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya st., Moscow, 117198, Russia
b M&S Decisions, 5 Naryshkinskaya al., Moscow, 125167, Russia
c Plekhanov Russian University of Economics, 3 Stremyanny per., Moscow, 117997, Russia
d Semenov Institute of Chemical Physics, 4 Kosygin st., Moscow, 119991, Russia
e Institut Camille Jordan, UMR 5208 CNRS, University Lyon 1, 69622 Villeurbanne, France
f INRIA Team Dracula, INRIA Lyon La Doua, 69603 Villeurbanne, France
Full-text PDF (838 kB) Citations (2)
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Abstract: In this work, we develop a model of the immune response to respiratory viral infections taking into account some particular properties of the SARS-CoV-2 infection. The model represents a system of ordinary differential equations for the concentrations of epithelial cells, immune cells, virus and inflammatory cytokines. Conventional analysis of the existence and stability of stationary points is completed by numerical simulations in order to study dynamics of solutions. Behavior of solutions is characterized by large peaks of virus concentration specific for acute respiratory viral infections.
At the first stage, we study the innate immune response based on the protective properties of interferon secreted by virus-infected cells. On the other hand, viral infection down-regulates interferon production. Their competition can lead to the bistability of the system with different regimes of infection progression with high or low intensity. In the case of infection out break, the incubation period and the maximal viral load depend on the initial viral load and the parameters of the immune response. In particular, increase of the initial viral load leads to shorter incubation period and higher maximal viral load.
In order to study the emergence and dynamics of cytokine storm, we consider proinflammatory cytokines produced by cells of the innate immune response. Depending on parameters of the model, the system can remain in the normal inflammatory state specific for viral infections or, due to positive feedback between inflammation and immune cells, pass to cytokine storm characterized by excessive production of proinflammatory cytokines. Furthermore, inflammatory cell death can stimulate transition to cytokine storm. However, it cannot sustain it by itself without the innate immune response. Assumptions of the model and obtained results are in qualitative agreement with the experimental and clinical data.
Keywords: innate immune response, cytokine storm, mathematical modelling.
Funding agency Grant number
Ministry of Science and Higher Education of the Russian Federation 075-03-2020-223/3 (FSSF-2020-0018)
This work is supported by the Ministry of Science and Higher Education of the Russian Federation: agreement no. 075-03- \2020-223/3 (FSSF-2020-0018).
Received: 21.03.2022
Revised: 10.05.2022
Accepted: 12.05.2022
Document Type: Article
UDC: 519.6
Language: Russian
Citation: M. Leon, A. A. Tokarev, V. A. Vol'pert, “Modelling of cytokine storm in respiratory viral infections”, Computer Research and Modeling, 14:3 (2022), 619–645
Citation in format AMSBIB
\Bibitem{LeoTokVol22}
\by M.~Leon, A.~A.~Tokarev, V.~A.~Vol'pert
\paper Modelling of cytokine storm in respiratory viral infections
\jour Computer Research and Modeling
\yr 2022
\vol 14
\issue 3
\pages 619--645
\mathnet{http://mi.mathnet.ru/crm987}
\crossref{https://doi.org/10.20537/2076-7633-2022-14-3-619-645}
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  • This publication is cited in the following 2 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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    Computer Research and Modeling
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