IDEAS home Printed from https://ideas.repec.org/a/aiy/journl/v6y2020i3p171-182.html
   My bibliography  Save this article

COVID-19 mortality rate in Russian regions: forecasts and reality

Author

Listed:
  • Lifshits, M. L.
  • Neklyudova, N. P.

Abstract

Relevance. COVID-19 is an extremely dangerous disease that not only spreads quickly, but is also characterized by a high mortality rate. Therefore, prediction of the number of deaths from the new coronavirus is an urgent task. Research objective. The aim of the study is to provide a more accurate estimate of the real number of coronavirus-related deaths in Russian regions. Data and methods. The main research method is econometric modeling. Comparison of various data was also applied. The authors’ calculations were based on Rosstat data, the data of the World Bank and specialized sites with coronavirus statistics in Russia and in the world. Results. We identified the factors affecting the COVID-19 mortality rates in various countries were identified, assessed how much the official Russian statistics underestimated mortality in Russian regions, and provided predictive estimates of mortality as a result of the pandemic. We also determined the number of additional coronavirus-induced deaths. Conclusions. The official data on COVID-19 mortality in Russia underestimate the actual numbers more than twofold. The number of direct and indirect victims of the pandemic in Russia at the end of July was approximately 43 thousand people.

Suggested Citation

  • Lifshits, M. L. & Neklyudova, N. P., 2020. "COVID-19 mortality rate in Russian regions: forecasts and reality," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 6(3), pages 171-182.
  • Handle: RePEc:aiy:journl:v:6:y:2020:i:3:p:171-182
    DOI: 10.15826/recon.2020.6.3.015
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10995/92820
    Download Restriction: no

    File URL: https://libkey.io/10.15826/recon.2020.6.3.015?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pavlov, Konstantin & Timiryanova, Venera & Yusupov, Kasim & Krasnoselskaya, Dina, 2022. "Анализ волн распространения Covid-19 в России [Analysis of Covid-19 wave distribution in Russia]," MPRA Paper 114637, University Library of Munich, Germany.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aiy:journl:v:6:y:2020:i:3:p:171-182. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Irina Turgel (email available below). General contact details of provider: https://edirc.repec.org/data/seurfru.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.