Problems of creating predictive models of the COVID19 coronavirus pandemic

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Abstract


Relevance. The article is devoted to creating prognostic models based on epidemiological and immunological data. Objective: to study the comparative dynamic epidemiological and immunological characteristics of patients with COVID-19. Materials and methods. Methodological approaches to the use of system analysis of epidemiological and immunological characteristics of patients with COVID-19 using multivariate analysis are described. The used technologies of computer-aided analysis systems, algorithms for recognizing, measuring and identifying the condition of patients, and methods of statistical data processing made it possible to create a universal information predictive model for calculating the dynamics of infectious diseases prone to generalization (pandemics), as well as to understand in which groups these new infectious diseases are most dangerous. Results and discussion. Using the methods of system analysis, the epidemiological and immunological aspects of predictive models of the coronavirus pandemic were evaluated using the most objective international data, which increased the information content of the analysis. Conclusions . Creating predictive epidemiological and immunological models of the pandemic is an urgent and promising task to combat the medical and social consequences of the spread of coronavirus infection in Russia.


About the authors

E. A. Levkova

Peoples’ Friendship University of Russia (RUDN University)

Author for correspondence.
Email: elenaalevkova@gmail.com
Moscow, Russian Federation

R. I. Sepiashvili

Peoples’ Friendship University of Russia (RUDN University)

Email: elenaalevkova@gmail.com
Moscow, Russian Federation

S. Z. Savin

Pacific National University

Email: elenaalevkova@gmail.com
Khabarovsk, Russian Federation

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