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Regular version of the site

Lecture by Alexandr Sokolov on "Balanced identification of the COVID-19 dynamic model: general biological patterns and country-specific social features"

On Wednesday, October 7 the scientific seminar of the International Centre of Decision Choice and Analysis was held. Alexandr Sokolov gave a lecture on "Balanced identification of the COVID-19 dynamic model: general biological patterns and country-specific social features"

Topic: Balanced identification of the COVID-19 dynamic model: general biological patterns and country-specific social features
Speakers: Alexander Sokolov (Institute for Information Transmission Problems (Kharkevich Institute), ICS RAS)

Annotation: The work considers the application of the technology of balanced identification for the numerical assessment of the correspondence of the mathematical model and experimental data. The technology uses a balanced identification method based on the principles of regularization and cross-validation (validation). It allowed to determine the applicability to this model on describing experimental data and calculating the values of unknown functions and parameters.
The work presents the model of the dynamics of the number of COVID-19 infections detected distributed by the duration of infection. The statistics on the infections detected (per day) in 7 populations are used as experimental data: Great Britain, Germany, Italy, Spain, France, Russia without Moscow and the Moscow region and Moscow with the Moscow region.
The model includes two groups of unknown functions: general biological that determine the interaction of the virus with the human body, and social controls that determine the impact of the society on humans. The functions obtained because of identification correspond to are consistent with the modern ideas about the processes that define the epidemic dynamics.
In this paper three modifications are considered:
- the first wave,
- antibodies (additional data - % of the population with antibodies),
- tests (additional data - the number of tests).