Volume 30, No 1, 2023, P. 40-66

UDC 519.8+518.25
O. I. Krivorotko, S. I. Kabanikhin, M. A. Bektemesov, M. I. Sosnovskaya, and A. V. Neverov
Simulation of COVID-19 propagation scenarios in the Republic of Kazakhstan based on regularization of agent model

Abstract:
An algorithm for modeling scenarios for new diagnosed cases of COVID-19 in the Republic of Kazakhstan is proposed. The algorithm is based on the treatment of incomplete epidemiological data and the inverse problem solving for the agent-based model (ABM) using a set of available epidemiological data. The main tool for building the ABMis the open library Covasim. In the event of a sudden change in the situation (appearance of a new strain, removal or introduction of restrictive measures, etc.), the model parameters are updated with additional information for the previous month (data assimilation). The inverse problem was solved by tree Parzen estimates optimization. As an example, two scenarios of COVID-19 propagation are given, calculated on December 12, 2021 for the period up to January 20, 2022. The scenario, which took into account the New Year holidays (published on December
12, 2021 on covid19-modeling.ru), almost coincided with what happened in reality (the error was 0,2%).
Tab. 3, illustr. 6, bibliogr. 33.

Keywords: agent oriented model, COVID-19, inverse problem, optimization, regularization, scenario, index of virus reproduction.

DOI: 10.33048/daio.2023.30.746

Olga I. Krivorotko ^1,2,3
Sergey I. Kabanikhin ^2,3
Maktagali A. Bektemesov ⁴
Mariya I. Sosnovskaya ³
Andrey V. Neverov ^1,3
1. Institute of Computational Mathematics and Mathematical Geophysics,
6 Acad. Lavrentiev Avenue, 630090 Novosibirsk, Russia
2. Sobolev Institute of Mathematics,
4 Acad. Koptyug Avenue, 630090 Novosibirsk, Russia
3. Novosibirsk State University,
2 Pirogov St., 630090 Novosibirsk, Russia
4. Abai Kazakh National Pedagogical University,
13 Dostyk Avenue, 050010 Almaty, Kazakhstan
e-mail: krivorotko.olya@mail.ru, ksi52@mail.ru, maktagali@mail.ru, m.sosnovskaya@alumni.nsu.ru, a.neverov@g.nsu.ru

Received July 4, 2022
Revised September 27, 2022
Accepted September 28, 2022

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