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This article is cited in 32 scientific papers (total in 32 papers)
Mathematical modeling and forecasting of COVID-19 in
Moscow and Novosibirsk region
O. I. Krivorotkoabc, S. I. Kabanikhincba, N. Yu. Zyatkovb, A. Yu. Prikhodkobca, N. M. Prokhoshinab, M. A. Shishlenincab a Mathematical Center in Akademgorodok, Novosibirsk, Russia
b Novosibirsk State University, Novosibirsk, Russia
c Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch,
Russian Academy of Sciences, Novosibirsk, Russia
Abstract:
We investigate the inverse problems of finding unknown parameters of the SEIR-HCD and SEIR-D mathematical models of the spread of COVID-19 coronavirus infection based on additional information about the
number of detected cases, mortality, self-isolation coefficient and tests performed for the city of Moscow and
the Novosibirsk region since 23.03.2020. In the SEIR-HCD model, the population is divided into seven, and in
SEIR-D - into five groups with similar characteristics and with transition probabilities depending on a specific
region. An analysis of the identifiability of the SEIR-HCD mathematical model was made, which revealed the
least sensitive unknown parameters as related to additional information. The task of determining parameters
is reduced to the minimization of objective functionals, which are solved by stochastic methods (simulated annealing, differential evolution, genetic algorithm). Prognostic scenarios for the disease development in Moscow
and in the Novosibirsk region were developed and the applicability of the developed models was analyzed.
Key words:
mathematical modeling, pandemic, COVID-19, SIER-HCD, SIER-D, scenarios, inverse problem, identifiability, optimization, differential evolution, annealing simulation, genetic algorithm, Moscow,
Novosibirsk region.
Received: 20.07.2020 Revised: 30.07.2020 Accepted: 30.07.2020
Citation:
O. I. Krivorotko, S. I. Kabanikhin, N. Yu. Zyatkov, A. Yu. Prikhodko, N. M. Prokhoshin, M. A. Shishlenin, “Mathematical modeling and forecasting of COVID-19 in
Moscow and Novosibirsk region”, Sib. Zh. Vychisl. Mat., 23:4 (2020), 395–414; Num. Anal. Appl., 13:4 (2020), 332–348
Linking options:
https://www.mathnet.ru/eng/sjvm756 https://www.mathnet.ru/eng/sjvm/v23/i4/p395
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