Geodesic
Mathematical modelling of COVID-19 incidence in~Moscow with an agent-based model
Diskretnyj analiz i issledovanie operacij, Tome 30 (2023) no. 2, pp. 15-47

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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
Mots-clés : Omicron strain, vaccination. 
@article{DA_2023_30_2_a1,
     author = {V. V. Vlasov and A. M. Deryabin and O. V. Zatsepin and G. D. Kaminskiy and E. V. Karamov and A. L. Karmanov and S. N. Lebedev and G. N. Rykovanov and A. V. Sokolov and N. A. Teplykh and A. S. Turgiyev and K. E. Khatuntsev},
     title = {Mathematical modelling of {COVID-19} incidence {in~Moscow} with an agent-based model},
     journal = {Diskretnyj analiz i issledovanie operacij},
     pages = {15--47},
     publisher = {mathdoc},
     volume = {30},
     number = {2},
     year = {2023},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/DA_2023_30_2_a1/}
}
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V. V. Vlasov; A. M. Deryabin; O. V. Zatsepin; G. D. Kaminskiy; E. V. Karamov; A. L. Karmanov; S. N. Lebedev; G. N. Rykovanov; A. V. Sokolov; N. A. Teplykh; A. S. Turgiyev; K. E. Khatuntsev. Mathematical modelling of COVID-19 incidence in~Moscow with an agent-based model. Diskretnyj analiz i issledovanie operacij, Tome 30 (2023) no. 2, pp. 15-47. http://geodesic.mathdoc.fr/item/DA_2023_30_2_a1/