Molecular Genetic Monitoring and Digital Transformation Technologies in Modern Epidemiology

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Abstract

The pandemic of a new coronavirus infection has become a serious challenge for the health system of all countries, so as of May 2023, 766 million confirmed cases of the disease and more than 6.9 million deaths have been registered in the world. More than 22 million cases and 398 thousand deaths from a new coronavirus infection have been registered in the Russian Federation. The rapidly changing epidemiological situation necessitated the systematization of the material for analytical work. The need to create special tools for aggregating an array of heterogeneous information has become obvious. The high rate of accumulation of mutations in the genome of the pathogen made it necessary to study circulating genovariants both from the standpoint of their escape from postmorbid and postvaccinal immunity, and from the point of view of the characteristics of the epidemic process caused by individual variants of the virus and their significance for practical health care and the organization of antiepidemic measures. The significant heterogeneity in terms of population density, geographical and economic conditions of the constituent entities of the Russian Federation necessitated the organization of work on the implementation of continuous molecular genetic monitoring of the variability of the COVID-19 pathogen. The active development of computing technologies and the challenges faced by the epidemiological surveillance system during the COVID-19 pandemic created the prerequisites for the rapid development of the process of digital transformation in epidemiology. Three platforms were created on the basis of Central Research Institute of Epidemiology — the Russian data aggregation system VGARus, SOLAR and an analytical platform for analyzing the epidemiological situation regarding the new coronavirus infection based on the Superset program, which were the main tools for epidemiological monitoring of the new coronavirus infection.

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About the authors

Vasily G. G. Akimkin

Central Research Institute of Epidemiology

Email: vgakimkin@yandex.ru
ORCID iD: 0000-0003-4228-9044
SPIN-code: 4038-7455

MD, PhD, Professor, Academician of the RAS

Russian Federation, 3a Novogireevskaya Str., Moscow, 111123

Kamil F. Khafizov

Central Research Institute of Epidemiology

Email: khafizov@cmd.su
ORCID iD: 0000-0001-5524-0296
SPIN-code: 9082-5749

PhD in Biology

Russian Federation, 3a Novogireevskaya Str., Moscow, 111123

Dmitry V. Dubodelov

Central Research Institute of Epidemiology

Email: dubodelov@cmd.su
ORCID iD: 0000-0003-3093-5731
SPIN-code: 4860-7909

MD, PhD, Senior Research Associate

Russian Federation, 3a Novogireevskaya Str., Moscow, 111123

Evgeny M. Voronin

Central Research Institute of Epidemiology

Email: emvoronin@yandex.ru
ORCID iD: 0000-0001-5925-7757
SPIN-code: 8153-8179
Russian Federation, 3a Novogireevskaya Str., Moscow, 111123

Anna S. Cherkashina

Central Research Institute of Epidemiology

Email: cherkashina@pcr.ms
ORCID iD: 0000-0001-7970-7495
SPIN-code: 7854-7358

 PhD in Chemistry

Russian Federation, 3a Novogireevskaya Str., Moscow, 111123

Svetlana V. Ugleva

Central Research Institute of Epidemiology

Author for correspondence.
Email: uglevas@bk.ru
ORCID iD: 0000-0002-1322-0155
SPIN-code: 8840-5814

MD, PhD, Professor

Russian Federation, 3a Novogireevskaya Str., Moscow, 111123

Denis V. Stratulat

Central Research Institute of Epidemiology

Email: stratylat@cmd.su
ORCID iD: 0000-0003-0988-4466
Russian Federation, 3a Novogireevskaya Str., Moscow, 111123

Alexander А. Samsonov

Central Research Institute of Epidemiology

Email: samsonov@cmd.su
ORCID iD: 0009-0007-8036-1883
Russian Federation, 3a Novogireevskaya Str., Moscow, 111123

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