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Local Factors of COVID-19 Severity in Russian Urban Areas

Author

Listed:
  • R. V. Goncharov

    (Faculty of Urban and Regional Development, HSE University)

  • E. A. Kotov

    (Faculty of Urban and Regional Development, HSE University)

  • V. A. Molodtsova

    (Faculty of Urban and Regional Development, HSE University)

Abstract

The COVID-19 pandemic has demonstrated that the lack of consideration of the local specifics of territories—the specifics of socioeconomic interactions, characteristics of the labor market—when developing measures to respond to epidemiological threats leads to serious social or economic consequences. The creation of a typology of municipalities (in this study of urban okrugs) makes it possible to more accurately select measures to regulate socioeconomic interactions in the event of future complications of the epidemiological situation. Clustering of municipalities according to a set of local factors that significantly explain the severity of the pandemic in its first year made it possible to identify three types of urban okrugs, differing both in population size and intensity of socioeconomic interactions: these are key service centers with a high intensity of interactions, local centers with medium intensity of interactions, and small cities with low intensity of interactions.

Suggested Citation

  • R. V. Goncharov & E. A. Kotov & V. A. Molodtsova, 2024. "Local Factors of COVID-19 Severity in Russian Urban Areas," Regional Research of Russia, Springer, vol. 14(2), pages 227-239, June.
  • Handle: RePEc:spr:rrorus:v:14:y:2024:i:2:d:10.1134_s2079970524600082
    DOI: 10.1134/S2079970524600082
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    References listed on IDEAS

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    1. Andrés Rodríguez‐Pose & Chiara Burlina, 2021. "Institutions and the uneven geography of the first wave of the COVID‐19 pandemic," Journal of Regional Science, Wiley Blackwell, vol. 61(4), pages 728-752, September.
    2. Maria N. Makarova & Olga A. Pyshmintseva, 2021. "Excess mortality in Russian regions during the COVID-19 pandemic," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 7(4), pages 225-234.
    3. M. R. Martines & R. V. Ferreira & R. H. Toppa & L. M. Assunção & M. R. Desjardins & E. M. Delmelle, 2021. "Detecting space–time clusters of COVID-19 in Brazil: mortality, inequality, socioeconomic vulnerability, and the relative risk of the disease in Brazilian municipalities," Journal of Geographical Systems, Springer, vol. 23(1), pages 7-36, January.
    4. Jerzy Bański & Marcin Mazur & Wioletta Kamińska, 2021. "Socioeconomic Conditioning of the Development of the COVID-19 Pandemic and Its Global Spatial Differentiation," IJERPH, MDPI, vol. 18(9), pages 1-15, April.
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