Comparison of Two Mean Field Approaches to Modeling An Epidemic Spread Научная публикация
Журнал |
Journal of Optimization Theory and Applications
ISSN: 0022-3239 , E-ISSN: 1573-2878 |
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Вых. Данные | Год: 2025, Том: 204, Номер статьи : 39, Страниц : 33 DOI: 10.1007/s10957-024-02604-1 | ||||
Ключевые слова | Mean field models · Epidemic models · SIR models · COVID-19 | ||||
Авторы |
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Организации |
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Информация о финансировании (1)
1 | Институт математики им. С.Л. Соболева СО РАН | FWNF-2024-0002 |
Реферат:
This paper describes and compares two approaches to modeling the spread of an epidemic based on the mean field theory, both with each other and with the original epidemiological SIR model. The first mean field approach is a model, in which an isolation strategy for each epidemiological group (Susceptible, Infected, and Removed) is chosen as an optimal control. The second is another mean field model, in which isolation strategy is common for the entire population. The considered models have been compared analytically, their sensitivity analysis has been carried out and their predictive capabilities have been estimated using sets of synthetic and real data. The well-known epidemiological SIR model is a part of comparison too. For one of the mean field models, its finite-difference analogue has been devised. The models have also been assessed in terms of their applicability for predicting a viral epidemic spread.
Библиографическая ссылка:
Petrakova V.
, Krivorotko O.
Comparison of Two Mean Field Approaches to Modeling An Epidemic Spread
Journal of Optimization Theory and Applications. 2025. V.204. 39 :1-33. DOI: 10.1007/s10957-024-02604-1 WOS Scopus OpenAlex
Comparison of Two Mean Field Approaches to Modeling An Epidemic Spread
Journal of Optimization Theory and Applications. 2025. V.204. 39 :1-33. DOI: 10.1007/s10957-024-02604-1 WOS Scopus OpenAlex
Даты:
Поступила в редакцию: | 3 мая 2024 г. |
Принята к публикации: | 19 дек. 2024 г. |
Опубликована в печати: | 23 янв. 2025 г. |
Опубликована online: | 23 янв. 2025 г. |
Идентификаторы БД:
Web of science: | WOS:001405107900008 |
Scopus: | 2-s2.0-85217763539 |
OpenAlex: | W4406775054 |
Цитирование в БД:
Пока нет цитирований