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Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki, 2021, Volume 61, Number 3, Pages 400–412
DOI: https://doi.org/10.31857/S0044466921030169 (Mi zvmmf11209) 		 
This article is cited in 10 scientific papers (total in 10 papers)

Ordinary differential equations

Reduced SIR model of COVID-19 pandemic

S. I. Vinitskyab, A. A. Guseva, V. L. Derbovc, P. M. Krasovitskiid, F. M. Pen'kove, G. Chuluunbaatarab

a Joint Institute for Nuclear Research, Dubna, Moscow region
b Peoples' Friendship University of Russia, Moscow
c Saratov State University
d Institute of Nuclear Physics, National Nuclear Center, Republic of Kazakhstan
e Al-Farabi Kazakh National University
Citations (10)
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DOI: https://doi.org/10.31857/S0044466921030169
Abstract: We propose a mathematical model of COVID-19 pandemic preserving an optimal balance between the adequate description of a pandemic by SIR model and simplicity of practical estimates. As base model equations, we derive two-parameter nonlinear first-order ordinary differential equations with retarded time argument, applicable to any community (country, city, etc.).The presented examples of modeling the pandemic development depending on two parameters: the time of possible dissemination of infection by one virus carrier and the probability of contamination of a healthy population member in a contact with an infected one per unit time, e.g., a day, is in qualitative agreement with the dynamics of COVID-19 pandemic. The proposed model is compared with the SIR model.
Key words: mathematical model, COVID-19 pandemic, first-order nonlinear ordinary differential equations, SIR model.
Funding agency Grant number
Ministry of Education and Science of the Russian Federation
Grant of Plenipotentiary of the Republic of Kazakhstan in JINR
Russian Foundation for Basic Research 20-51-44001
The work was partially supported by the RUDN University Program 5-100, grant of Plenipotentiary of the Republic of Kazakhstan in JINR (2020), and the Russian Foundation for Basic Research and the Ministry of Education, Culture, Science and Sports of Mongolia (grant no. 20-51-44001).
Received: 12.09.2020
Revised: 19.10.2020
Accepted: 18.11.2020
English version:
Computational Mathematics and Mathematical Physics, 2021, Volume 61, Issue 3, Pages 376–387
DOI: https://doi.org/10.1134/S0965542521030155
Bibliographic databases:
Document Type: Article
UDC: 51-73
Language: Russian
Citation: S. I. Vinitsky, A. A. Gusev, V. L. Derbov, P. M. Krasovitskii, F. M. Pen'kov, G. Chuluunbaatar, “Reduced SIR model of COVID-19 pandemic”, Zh. Vychisl. Mat. Mat. Fiz., 61:3 (2021), 400–412; Comput. Math. Math. Phys., 61:3 (2021), 376–387
Citation in format AMSBIB
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\by S.~I.~Vinitsky, A.~A.~Gusev, V.~L.~Derbov, P.~M.~Krasovitskii, F.~M.~Pen'kov, G.~Chuluunbaatar
\paper Reduced SIR model of COVID-19 pandemic
\jour Zh. Vychisl. Mat. Mat. Fiz.
\yr 2021
\vol 61
\issue 3
\pages 400--412
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\crossref{https://doi.org/10.31857/S0044466921030169}
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\jour Comput. Math. Math. Phys.
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\vol 61
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\pages 376--387
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    • This publication is cited in the following 10 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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    		Журнал вычислительной математики и математической физики Computational Mathematics and Mathematical Physics
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