О математическом моделировании COVID-19 Full article
| Journal |
Сибирские электронные математические известия (Siberian Electronic Mathematical Reports)
, E-ISSN: 1813-3304 |
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| Output data | Year: 2023, Volume: 20, Number: 2, Pages: 1211-1268 Pages count : 58 DOI: 10.33048/semi.2023.20.075 | ||
| Tags | epidemiology, COVID-19, time-series models, SIR, agentbased models, mean field games, inverse problems, forecasting | ||
| Authors |
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| Affiliations |
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Funding (1)
| 1 | Russian Science Foundation | 23-71-10068 |
Abstract:
The mathematical models for analysis and forecasting of COVID-19 pandemic based on time-series models, differential equations (SIR models based on odinary, partial and stochastic differential equations), agent-based models, mean field games and its combinations are considered. Inverse problems for mathematical models in epidemiology of COVID-19 are formulated in the variational form. The numerical results of modeling and scenarios of COVID-19 propagation in Novosibirsk region are demonstrated and discussed. The epidemiology parameters of COVID-19 propagation in Novosibirsk region (contagiosity, hospitalization and mortality rates, asymptomatic cases) are identified. The combination of differential and agent-based models increases the quality of forecast scenarios.
Cite:
Криворотько О.И.
, Кабанихин С.И.
О математическом моделировании COVID-19
Сибирские электронные математические известия (Siberian Electronic Mathematical Reports). 2023. Т.20. №2. С.1211-1268. DOI: 10.33048/semi.2023.20.075 WOS Scopus
О математическом моделировании COVID-19
Сибирские электронные математические известия (Siberian Electronic Mathematical Reports). 2023. Т.20. №2. С.1211-1268. DOI: 10.33048/semi.2023.20.075 WOS Scopus
Dates:
| Submitted: | Dec 12, 2022 |
| Published print: | Nov 21, 2023 |
| Published online: | Nov 21, 2023 |
Identifiers:
| Web of science: | WOS:001102184700001 |
| Scopus: | 2-s2.0-85179653188 |