UDC 519.6
1 Educational and Scientific Institute of Automatics, Cybernetics, and Computer Engineering of the National University of Water and Environmental Engineering, Rivne, Ukraine
svbaranovsky@gmail.com
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2 Educational and Scientific Institute of Automatics, Cybernetics, and Computer Engineering of the National University of Water and Environmental Engineering, Rivne, Ukraine
abomba@ukr.net
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GENERALIZATION OF THE ANTIVIRAL IMMUNE RESPONSE MODEL FOR COMPLEX
CONSIDERATION OF DIFFUSION PERTURBATIONS, BODY TEMPERATURE RESPONSE,
AND LOGISTIC ANTIGENS POPULATION DYNAMICS
Abstract. The Marchuk–Petrov mathematical model of antiviral immune response is generalized for complex consideration of diffusion perturbations, concentrated influences, body temperature response, and logistic population dynamics of viral elements and antibodies to the development of infectious disease. A step-by-step procedure for numerically asymptotic solution of the corresponding singularly perturbed problems with delays is developed. The authors present the results of computer simulation, which illustrate the “model” reduction of the maximum level of antigens in the epicenter of infection due to their diffusion “scattering,” body temperature response, and logistic population dynamics of viruses on the nature of infectious disease, including the presence of concentrated sources of antigens. It is emphasized that such a systemic effect of these factors can reduce the initial supercritical concentration of antigens to a level after which their neutralization and excretion will be provided by the existing level of immune protection, which is important in deciding whether to use external “therapeutic” effects.
Keywords: model of antiviral immune response, dynamic systems with delay, asymptotic methods, singularly perturbed problems, concentrated influences, logistics dynamics.
FULL TEXT
REFERENCES
- Marchuk G.L. Mathematical models of immune response in infectious diseases. Dordrecht: Kluwer Press, 1997. 350 p. https://doi.org/10.1007/978-94-015-8798-3.
- Nowak M.A., May R.M. Virus dynamics. Mathematical principles of immunology and virology. Oxford University Press, 2000. 237 p.
- Wodarz D. Killer cell dynamics. Mathematical and computational approaches to immunology. New York: Springer, 2007. 220 p. https://doi.org/10.1007/978-0-387-68733-9.
- Bomba A.Ya., Baranovsky S.V., Pasichnyk M.S., Pryshchepa O.V. Modeling small-scale spatial distributed influences on the development of infectious disease process. Mathematical Modeling and Computing. 2020. Vol. 7, N 2. P. 310–321. https://doi.org/10.23939/mmc2020.02.310.
- Baranovsky S.V., Bomb A.Ya. Generalization of the mathematical model of the Marchuk – Petrov antiviral immune response taking into account the influence of small spatially distributed diffusion perturbations. Mathematical and computer modeling. Ser. Technical sciences. 2020. Iss. 21. p. 5–24. https://doi.org/10.32626/2308-5916.2020-21.5-24.
- Bomba A.Ya., Baranovsky S.V., Pasichnyk M.S., Pryshchepa O.V. Modelling of the infectious disease process with taking into account of small-scale spatially distributed influences. Proc. of the 15th International Scientific and Technical Conference on Computer Sciences and Information Technologies (23–26 Sept., 2020, Lviv–Zbarazh, Ukraine). IEEE, 2020. Vol. 2. P. 62–65. https://doi.org/10.1109/CSIT49958.2020.9322047.
- Bomba A.Ya., Baranovsky SV Modeling of small spatially distributed effects on the dynamics of infectious disease in conditions such as pharmacotherapy. Zhurnal obchyslyuvalʹnoyi ta prykladnoyi matematyky. 2020. N 1 (133). P. 5–17. https://doi.org/10.17721/ 2706-9699.2020.1.01.
- Bomba А., Baranovskii S., Pasichnyk M., Malash K. Modeling of infectious disease dynamics under the conditions of spatial perturbations and taking into account impulse effects. Proc. of the 3rd International Conference on Informatics & Data-Driven Medicine (19–21 Nov., 2020, Vxj, Sweden). CEUR Workshop Proceedings, 2020. Vol. 2753. P. 119–128. URL: https://doi.org/10.15407/dopovidi2021.03.003.
- Baranovsky S.V., Bomba A.Ya., Lyashko S.I. Decision-making in modeling the dynamics of an infectious disease, taking into account diffusion perturbations and concentrated effects. Problemy upravleniya i informatiki. 2021. N 3. P. 115–129.
- Baranovsky S.V., Bomba A.Y., Lyashko S.I. Modeling the effect of diffusion perturbations on the development of infectious disease taking into account convection and immunotherapy. Dop. Nats. Acad. Nauk Ukr. 2021. N 3. P. 17–25. https://doi.org/10.15407/dopovidi2021.03.003.
- Bomba А., Baranovsky S., Blavatska O., Bachyshyna L. Modification of infection disease model to take into account diffusion perturbation in the conditions of temperature reaction of the organism. Proc. of the 4th International Conference on Informatics & Data-Driven Medicine, (19–21 Nov., 2021, Valencia, Spain). CEUR Workshop Proceedings, 2021. Vol. 3038. P. 93–99. URL: http://ceur-ws.org/Vol-3038/short3.pdf .
- Klyushin D.A., Lyashko S.I., Lyashko N.I., Bondar O.S., Tymoshenko A.A. Generalized optimization of processes of drug transport in tumors. Cybernetics and System Analisys. 2020. Vol. 56, N 5. P. 758–765. https://doi.org/10.1007/s10559-020—00296-0.
- Sandrakov G.V., Lyashko S.I., Bondar E.S., Lyashko N.I. Modeling and optimization of microneedle systems. Journal of Automation and Information Sciences. 2019. Vol. 51, Iss. 6. P. 1–11. https://doi.org/10.1615/JAutomatInfScien.v51.i6.10.
- Lyashko S.I., Semenov V.V. Controllability of linear distributed systems in classes of generalized actions. Cybernetics and Systems Analysis. 2001. Vol. 37, N 1. P. 13–32. https://doi.org/10.1023/A:1016607831284.
- Lyashko S.I. Man’kovskii A.A. Controllability of impulse parabolic systems. Automation and Remote Control. 1991. Vol. 52, N 9. P. 1233–1238.
- Lyashko S.I. Klyushin D.A. Palienko L.I. Simulation and generalized optimization in pseudohyperbolical systems. Journal of Automation and Information Sciences. 2000. Vol. 32, Iss. 5. P. 108–117. https://doi.org/10.1615/JAutomatInfScien.v32.i5.80.
- Bomba A.Ya., Fursachyk O.A. Inverse singularly perturbed problems of the convection-diffusion type in quadrangular curvilinear domains. Journal of Mathematical Sciences. 2010. Vol. 171. Iss. 4. P. 490–498. https://doi.org/10.1007/s10958-010-0152-2.
- Bomba A.Ya. Asymptotic method for approximately solving a mass transport problem for flow in a porous medium. Ukrainian Mathematical Journal. 1982. Vol. 34, Iss. 4. P. 400–403.
- Petryk M.R., Khimich A., Petryk M.M., Fraissard J. Experimental and computer simulation studies of dehydration on microporous adsorbent of natural gas used as motor fuel. Fuel. 2019. Vol. 239. P. 1324–1330. https://doi.org/10.1016/j.fuel.2018.10.134.
- Nakonechnyi A.G., Kapustian E.A., Chikrii A.A. Control of impulse systems in conflict situation. Journal of Automation and Information Sciences. 2019. Vol. 51, Iss. 9. P. 1–11. https://doi.org/10.1615/JAutomatInfScien.v51.i9.10.
- Chikrii A., Petryshyn R., Cherevko I., Bigun Ya. Method of resolving functions in the theory of conflict-controlled processes. Advanced Control Techniques in Complex Engineering Systems: Theory and Applications. Studies in Systems, Decision and Control. 2019. Vol. 203. P. 3–33. https://doi.org/10.1007/978-3-030-21927-7_1.
- Golovynskyi A., Sergienko I., Tulchinskyi V., Malenko A., Bandura O., Gorenko S., Roganova O., Lavrikova O. Development of SCIT supercomputers family created at the V.M. Glushkov Institute of Cybernetics, NAS of Ukraine, in 2002–2017. Cybernetics and Systems Analysis. 2017. Vol. 53, N 4. P. 600–604. https://doi.org/10.1007/s10559-017-9962-2.
- Zadiraka V.K. Using reserves of computing optimization to solve complex problems. Cybernetics and Systems Analysis. 2019. Vol. 55, N 1. P. 40–54. https://doi.org/10.1007/s10559-019-00111-0.