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JOURNALS // Diskretnyi Analiz i Issledovanie Operatsii // Archive

Diskretn. Anal. Issled. Oper., 2023 Volume 30, Issue 2, Pages 15–47 (Mi da1320)

Mathematical modelling of COVID-19 incidence in Moscow with an agent-based model

V. V. Vlasova, A. M. Deryabina, O. V. Zatsepina, G. D. Kaminskiyb, E. V. Karamovcb, A. L. Karmanova, S. N. Lebedeva, G. N. Rykovanova, A. V. Sokolova, N. A. Teplykha, A. S. Turgiyevcb, K. E. Khatuntseva

a Russian Federal Nuclear Center — Zababakhin All-Russian Research Institute of Technical Physics, 13 Vasilyev Street, 456770 Snezhinsk, Russia
b National Medical Research Center for Phthisiopulmonology and Infectious Diseases, 4 Dostoevskiy Street, 127473 Moscow, Russia
c Gamaleya National Research Center for Epidemiology and Microbiology, 18 Gamaleya Street, 123098 Moscow, Russia

Abstract: The outbreak of the COVID-19 pandemic created an emergency situation in the public health system in Russia and in the world, which entailed the need to develop tools for predicting the progression of the pandemic and assessing the potential interventions. In the present day context, numerical simulation is actively used to solve such problems. The paper considers a COVID-19 agent-based megalopolis model. The model was developed in 2020 and was further refined in subsequent years. The capabilities of the model include the description of simultaneous spread of several virus strains and taking into account data on vaccination and population activity. The model parameters are calculated using statistical data on the daily number of newly diagnosed COVID-19 cases. The application of the model to describe the epidemiological situation in Moscow in 2021 and early 2022 was demonstrated. The capability for building predictions for 1–3 months was shown, taking into account the emergence of new SARS-CoV-2 variants, i. e. the Delta and Omicron strains. Tab. 3, illustr. 10, bibliogr. 64.

Keywords: COVID-19 pandemic, numerical simulation, agent-based model, COVID-19 epidemic development prediction, SARS-CoV-2 variants, Delta strain, Omicron strain, vaccination.

UDC: 519.8+518.25

Received: 20.12.2022
Revised: 13.02.2023
Accepted: 14.02.2023

DOI: 10.33048/daio.2023.30.761



© Steklov Math. Inst. of RAS, 2024