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JOURNALS // Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki // Archive

Zh. Vychisl. Mat. Mat. Fiz., 2021 Volume 61, Number 3, Pages 400–412 (Mi zvmmf11209)

This article is cited in 11 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

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.

UDC: 51-73

Received: 12.09.2020
Revised: 19.10.2020
Accepted: 18.11.2020

DOI: 10.31857/S0044466921030169


 English version:
Computational Mathematics and Mathematical Physics, 2021, 61:3, 376–387

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© Steklov Math. Inst. of RAS, 2024