Several options of the stochastic SIR epidemics model with limited treatment are proposed. For these methods, the efficiency of different vaccination strategies is demonstrated, and a method for obtaining the optimal vaccination strategy minimizing the cost functional is proposed.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
O. V. Bogdanov and P. S. Knopov, “Stochastic models in the problems of predicting the epidemiological situation,” Cybern. Syst. Analysis, Vol. 58, No. 1, 58–64 (2022). https://doi.org/10.1007/s10559-022-00435-4.
M. Ishikawa, “Optimal vaccination strategy under saturated treatment using the stochastic SIR model,” Trans. Inst. of Systems, Control and Information Eng., Vol. 26, No. 11, 382–388 (2013). https://doi.org/10.5687/iscie.26.382.
R. Pearl, The Biology of Population Growth, A. A. Knopf, New York (1925).
B. Øksendal, Stochastic Differential Equations: An Introduction with Applications, 6th ed., Springer, Berlin–Heidelberg (2010). https://doi.org/10.1007/978-3-642-14394-6.
W. H. Flemming, “Some Markovian optimization problems,” J. Math. Mech., Vol. 12, No. 1, 131–140 (1963).
Author information
Authors and Affiliations
Corresponding author
Additional information
The research was partially supported by the National Research Foundation of Ukraine, Grant #2020.02.0121, and a joint project between IIASA (Austria) and the National Academy of Sciences of Ukraine.
Translated from Kibernetyka ta Systemnyi Analiz, No. 2, March–April, 2023, pp. 166–172.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Bogdanov, O. Variants of the Stochastic Sir Models and Vaccination Strategies. Cybern Syst Anal 59, 325–330 (2023). https://doi.org/10.1007/s10559-023-00566-2
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10559-023-00566-2