Влияние коронавирусной инфекции на социально-экономические показатели региона
Работая с нашим сайтом, вы даете свое согласие на использование файлов cookie. Это необходимо для нормального функционирования сайта, показа целевой рекламы и анализа трафика. Статистика использования сайта отправляется в «Яндекс» и «Google»
Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

The impact of coronavirus infection on the socio-economic indicators of the region

idPecherina A.V.

UDC 004
DOI: 10.26102/2310-6018/2022.38.3.028

  • Abstract
  • List of references
  • About authors

The new coronavirus infection (COVID-19) which emerged in Wuhan, China, in early December 2019 quickly spread to almost every country in the world and shocked the global economy. This article highlights the most important problems that are caused by the coronavirus pandemic. The author discusses the impact of the new coronavirus infection Covid-19 on some socio-economic indicators of a particular region of the Russian Federation as well as the Russian Federation as a whole. In order to do that, an analytical procedure was developed using Knime Analytics Platform (the free and open source data analysis platform), which, in turn, greatly simplified data processing and visualization of results. The platform makes it possible to develop reproducible and scalable workflows by integrating a wide range of analysis tools. The analysis was based on the data extracted from the website of the Center for Spatiotemporal Innovation at Harvard University (NSF Spatiotemporal Innovation Center) and the statistical data extracted from the website of the Federal State Statistics Service. We visualized the data and drew conclusions about COVID-2019 incidence rate and the cost of a constant set of consumer products and services for the purposes of inter-regional comparisons of purchasing power.

1. Big Data Association. Available from: https://rubda.ru/deyatelnost/strategiya/ (date of accessed on: 26.02.2022). (In Russ.).

2. Voronov V.I., Voronova L.I., Usachev V.A. Data Mining – big data processing technologies: a tutorial. Moscow Technical University of Communications and Informatics; 2018. 47 p. (In Russ.).

3. Zhilenkova E.P., Zakharova D.V. Socio-economic development of regions: concept, factors and main statistical indicators. Sotsial'no-ekonomicheskoe razvitie Rossii i regionov v tsifrakh statistiki: Materialy VII mezhdunarodnoi nauchno-prakticheskoi konferentsii. 2021:183–187. (In Russ.).

4. Kuklina O. K., Pecherina A.V., Mikhailova E.A. Features of forecasting and modeling of regional socio-economic systems on the example of the formation of a multifactor model for forecasting passenger traffic in the Trans-Baikal Territory. Nauka i tekhnika transporta. 2020;(3):44–54. (In Russ.).

5. Kuznetsova I.A. Theory of systems and system analysis: workshop. Irkutsk, BSU Publishing House; 2017. 56 p. (In Russ.).

6. Ministry of Economic Development of the Russian Federation. Available from: https://www.economy.gov.ru/ (accessed on 25.01.2022). (In Russ.).

7. Kiseleva I.V., Larionova N.V., Grigorieva E.P. Peculiarities of circulation of respiratory viruses in pre- and pandemic influenza and COVID-19 periods. Infektsiya i immunitet. 2021;11(6):1009–1019. DOI: 10.15789/2220-7619-SFO-1662. (In Russ.).

8. Federal State Statistics Service. Rosstat. Available from: https://rosstat.gov.ru/emiss/ (accessed on 26.02.2022). (In Russ.).

9. Federal Service for Supervision of Consumer Rights Protection and Human Welfare. Rosstat. Available from: https://rosstat.gov.ru/emiss/ (accessed on 25.02.2022). (In Russ.).

10. Center for Spatio-Temporal Innovation at Harvard University. NSF Spatiotemporal Innovation Center. Available from: https://www.stcenter.net/ (accessed on 15.01.2022). (In Russ.).

Pecherina Alexandra Valerievna

ORCID | eLibrary |

Baikal State University

Irkutsk, Russia

Keywords: data analysis, data mining, covid-19, coronavirus infection, socio-economic indicators

For citation: Pecherina A.V. The impact of coronavirus infection on the socio-economic indicators of the region. Modeling, Optimization and Information Technology. 2022;10(3). Available from: https://moitvivt.ru/ru/journal/pdf?id=1213 DOI: 10.26102/2310-6018/2022.38.3.028 (In Russ).

374

Full text in PDF

Received 19.09.2022

Revised 26.09.2022

Accepted 28.09.2022

Published 28.09.2022