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This article is cited in 12 scientific papers (total in 12 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.
Received: 12.09.2020 Revised: 19.10.2020 Accepted: 18.11.2020
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
Linking options:
https://www.mathnet.ru/eng/zvmmf11209 https://www.mathnet.ru/eng/zvmmf/v61/i3/p400
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