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.
This work was supported by the Russian Science Foundation under project no. 18-71-10044
(problem statement, identifiability analysis, and numerical solution of the forecasting problem for mathematical model SEIR-HCD, Sections 1, 3, and 4), and the Mathematical Center in Akademgorodok
under agreement no. 075-15-2019-1675 with the Ministry of Science and Higher Education of the
Russian Federation (formulation and numerical solution of the inverse problem for mathematical model
SEIR-D, Sections 2 and 3).
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
\Bibitem{KriKabZya20}
\by O.~I.~Krivorotko, S.~I.~Kabanikhin, N.~Yu.~Zyatkov, A.~Yu.~Prikhodko, N.~M.~Prokhoshin, M.~A.~Shishlenin
\paper Mathematical modeling and forecasting of COVID-19 in
Moscow and Novosibirsk region
\jour Sib. Zh. Vychisl. Mat.
\yr 2020
\vol 23
\issue 4
\pages 395--414
\mathnet{http://mi.mathnet.ru/sjvm756}
\crossref{https://doi.org/10.15372/SJNM20200404}
\transl
\jour Num. Anal. Appl.
\yr 2020
\vol 13
\issue 4
\pages 332--348
\crossref{https://doi.org/10.1134/S1995423920040047}
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Linking options:
https://www.mathnet.ru/eng/sjvm756
https://www.mathnet.ru/eng/sjvm/v23/i4/p395
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