Abstract
The article is devoted to the analysis of the available mathematical models in epidemiology and the possibility of their modification. We note that the situation with the COVID-19 virus pandemic is characterized by several features not comprehensively studied in the existing models. For a rational response to existing challenges, it is necessary to have a predictive and analytical apparatus in the complex (national and regional scale) mathematical models with a planning horizon of 2 years (the expected period of mass production of vaccines). The article discusses the existing approaches to predicting the spread of the COVID-19 virus in Russia based on mathematical models of epidemics. The possibilities and limitations of the proposed approaches are considered. In the conditions of the Russian Federation, transport connectivity at the interregional and intraregional levels plays an important role, and for megalopolises - transport flows within large agglomerations and the age structure of the population. In contrast to previous pandemics and epidemics, public policy plays a significant role. The approach, which consist in building multi-agent models that combine the advantages of compartment models and models based on the Monte Carlo method (individually oriented) is proposed by the authors. It is planned to use compartment models to assess the dynamics of the process and individually-oriented models - at the level of individual territories and districts.
Highlights
The presented paper demonstrates a wide range of results that can be obtained using several modified SEER models
The formation of agent models in which the selected clusters interact with each other, and the behavior of the cluster continues to be described by SEER models
The authors propose to add economics-related models to the purely medical aspects
Summary
The SARS-COVID19 virus pandemic is an object of close study by both epidemiologists and specialists in data analysis and numerical modeling, since the high degree of informatization of developed countries allows to obtain open statistical information practically on the day of its registration.An analysis of the spread of viral infections is important both from a scientific point of view and from a practical viewpoint, since the volume of sick people in the population determines the burden on the health care system, makes it possible to estimate the required number of beds in hospitals, the amount of drugs consumed, the number of ventilators and medical personnel, the nature and severity of the applied restrictive measures.Mathematical modeling of these processes has been carried out since the 20s of the XX century, a modern highly mobile society, a developed healthcare system, the specificity of the COVID-19 virus as such sets the task of developing and verifying, if not completely new mathematical models in a significant way corrected model.the work is relevant, and the proposed approaches can be used for prognostic by government agencies, the leadership of medical institutions and the business community.Alexander Samarkin., et al Research of Approaches to Constructing Predictive Models of the Spread of Viral Diseases. An analysis of the spread of viral infections is important both from a scientific point of view and from a practical viewpoint, since the volume of sick people in the population determines the burden on the health care system, makes it possible to estimate the required number of beds in hospitals, the amount of drugs consumed, the number of ventilators and medical personnel, the nature and severity of the applied restrictive measures Mathematical modeling of these processes has been carried out since the 20s of the XX century, a modern highly mobile society, a developed healthcare system, the specificity of the COVID-19 virus as such sets the task of developing and verifying, if not completely new mathematical models in a significant way corrected model.
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