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

Marina L. Lifshits, Natalia P. Neklyudova


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.


COVID-19, regions of Russia, mortality rate, lethality, econometric modelin

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Al-Raeei, M. (2020). The forecasting of COVID-19 with mortality using SIRD epidemic model for the United States, Russia, China, and the Syrian Arab Republic. Aip Advances, 10(6). doi:10.1063/5.0014275

Anastassopoulou, C., Russo, L., Tsakris, A., & Siettos, C. (2020). Data-based analysis, modelling and forecasting of the COVID-19 outbreak. Plos One, 15(3). doi:10.1371/journal.pone.0230405

Aronov, I. Z., Maksimova, O. V., & Galkina, N. M. (2020). COVID-19 Highest Incidence Forecast in Russia Based on Regression Model. International Journal of Mathematical Engineering and Management Sciences, 5(5), 812-819. doi:10.33889/ijmems.2020.5.5.063

Chintalapudi, N., Battineni, G., & Amenta, F. (2020). COVID-19 virus outbreak forecasting of registered and recovered cases after sixty day lockdown in Italy: A data driven model approach. Journal of Microbiology Immunology and Infection, 53(3), 396-403. doi:10.1016/j.jmii.2020.04.004

Danilova, I. A. (2020). Morbidity and mortality due to COVID-19. The problem of data comparability. Demographic review, 7 (1), 6-26.

Drapkina O. M., Samorodskaya I. V., Sivtseva M. G., Ka -korina E. P., Briko N. I., Cherkasov S. N., Zinserling V. A., & Malkov P. G. (2020). COVID-19: urgent questions for estimating morbidity, prevalence, case fatality rate and mortality rate. Cardiovascular Therapy and Prevention,19(3):2585. (In Russ.) doi:10.15829/1728-8800-2020-2585

Dyer, O. (2020). Covid-19: Cases rise in Russia as health workers pay the price for PPE shortage. Bmj-British Medical Journal, 369. doi:10.1136/bmj.m1975

Ferraro, O. E., Puci, M. V., Montomoli, C., Rolesu, S., Cappai, S., & Loi, F. (2020). Official Data and Analytical Forecasts: Differences and Similarities Among Coronavirus Disease (COVID-19) Confirmed Cases and Deaths. Frontiers in Medicine, 7. doi:10.3389/fmed.2020.00239

Gao, Y., Zhang, Z., Yao, W., Ying, Q., Long, C., & Fu, X. (2020a). Forecasting the cumulative number of COVID-19 deaths in China: a Boltzmann function-based modeling study. Infection Control and Hospital Epidemiology, 41(7), 841-843. doi:10.1017/ice.2020.101

Gerli, A. G., Centanni, S., Miozzo, M. R., Virchow, J. C., Sotgiu, G., Canonica, G. W., & Soriano, J. B. (2020a). COVID-19 mortality rates in the European Union, Switzerland, and the UK: effect of timeliness, lockdown rigidity, and population density. Minerva medica. doi:10.23736/s0026-4806.20.06702-6

Haghani, M., Bliemer, M. C. J., Goerlandt, F., & Li, J. (2020a). The scientific literature on Coronaviruses, COVID-19 and its associated safety-related research dimensions: A scientometric analysis and scoping review. Safety Science, 129. doi:10.1016/j.ssci.2020.104806

Harapan, H., Itoh, N., Yufika, A., Winardi, W., Keam, S., Te, H., . . . Mudatsir, M. (2020). Coronavirus disease 2019 (COVID-19): A literature review. Journal of Infection and Public Health, 13(5), 667-673. doi:10.1016/j.jiph.2020.03.019

Lifshits, M.L., (2020). Regularities of the COVID-19 mortality level in the world and forecast of the number of death due to epidemic in Russia. Paper presented at the XI Ural Demographic Forum, Yekaterinburg, Institute of Economics UB RAS, RUSSIA. (In press).

Methodological Recommendations on the Coding and Selection of the Underlying Medical Condition in the Statistics of Morbidity and the Primary Cause of Death in the Statistics of Mortality in Relation to COVID-19 (Approved by the Ministry of Health of the Russian Federation on 05.27.2020). Russian Journal of Forensic Medicine. 2020;6(2):53–62. (In Russ.)

Middelburg, R. A., & Rosendaal, F. R. (2020). COVID-19: How to make between-country comparisons. International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 96, 477-481. doi:10.1016/j.ijid.2020.05.066

Onder, G., Rezza, G., & Brusaferro, S. (2020). Case-Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy. Jama-Journal of the American Medical Association, 323(18), 1775-1776. doi:10.1001/jama.2020.4683

Sanchez-Villegas, P., & Daponte Codina, A. (2020). Predictive models of the COVID-19 epidemic in Spain with Gompertz curves. [Modelos predictivos de la epidemia de COVID-19 en Espana con curvas de Gompertz.]. Gaceta sanitaria. doi:10.1016/j.gaceta.2020.05.005

Scafetta, N. (2020). Distribution of the SARS-CoV-2 Pandemic and Its Monthly Forecast Based on Seasonal Climate Patterns. International Journal of Environmental Research and Public Health, 17(10). doi:10.3390/ijerph17103493

Sebastiani, G., Massa, M., & Riboli, E. (2020). Covid-19 epidemic in Italy: evolution, projections and impact of government measures. European Journal of Epidemiology, 35(4), 341-345. doi:10.1007/s10654-020-00631-6

Semenova, Y., Glushkova, N., Pivina, L., Khismetova, Z., Zhunussov, Y., Sandybaev, M., & Ivankov, A. (2020). Epidemiological Characteristics and Forecast of COVID-19 Outbreak in the Republic of Kazakhstan. Journal of Korean Medical Science, 35(24). doi:10.3346/jkms.2020.35.e227

Singh, R. K., Rani, M., Bhagavathula, A. S., Sah, R., Rodriguez-Morales, A. J., Kalita, H., . . . Kumar, P. (2020). Prediction of the COVID-19 Pandemic for the Top 15 Affected Countries: Advanced Autoregressive Integrated Moving Average (ARIMA) Model. JMIR

Shojaee, S., Pourhoseingholi, M. A., Ashtari, S., Vahedian-Azimi, A., Asadzadeh-Aghdaei, H., & Zali, M. R. (2020). Predicting the mortality due to Covid-19 by the next month for Italy, Iran and South Korea; a simulation study. Gastroenterology and hepatology from bed to bench, 13(2), 177-179.

Varga, Z., Flammer, A. J., Steiger, P., Haberecker, M., Andermatt, R., Zinkernagel, A. S., . . . Moch, H. (2020). Endothelial cell infection and endotheliitis in COVID-19. Lancet, 395(10234), 1417-1418. doi:10.1016/s0140-6736(20)30937-5

Zemtsov, S. P. & Baburin, V. L. (2020). Risks of morbidity and mortality during the COVID-19 pandemic in Russian regions. Population and Economics 4(2), 158-181.

Vandoros, S. (2020). Excess mortality during the Covid-19 pandemic: Early evidence from England and Wales. Social Science & Medicine, 258, 4. doi:10.1016/j.socscimed.2020.113101


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