Movimiento de población natural y COVID-19: datos de Rusia
Keywords:
COVID-19 pandemic, demographics, vital movement, mortality, geopolitics
Abstract
The COVID-19 pandemic is highly infectious, so it paralyzed the health systems of many countries causing a high mortality rate. Official data on COVID-19 deaths at many sites are questioned, and the figures are considered several times higher than official data. In this sense, the objective of the study was to determine the impact of the COVID-19 pandemic on the natural movement of the population and, in addition, to evaluate the real mortality rate from COVID-19 in Russia from the construction of predictive mortality models. The study used data from the World Health Organization and the Statistical Service of the Federal State of Russia; se used linear and polynomial models to construct mortality models. The study revealed an underestimation of the official COVID-19 death rate by 2.4 to 6.8 times, depending on the data source. There was a sharp increase in mortality in Russia in 2020 among people over 50 years of age, and with the increase in age, mortality increased. The main reasons for the sharp increase in mortality were coronary heart disease, cerebrovascular diseases, and respiratory diseases, among others.
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References
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ONDER, Graziano; REZZA, Giovanni; BRUSAFERRO, Silvio. 2020. “Case- Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy” In: Jama-Journal of the American Medical Association. Vol. 323, No. 18, pp. 1775-1776.
ORAN, Daniel; TOPOL, Eric. 2020. “Prevalence of Asymptomatic SARS-CoV-2 Infection: A Narrative Review” In: Annals of internal medicine. Vol. 173, No. 5, pp. 362-367.
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VANDOROS, Sotiris. 2020. “Excess mortality during the Covid-19 pandemic: Early evidence from England and Wales” In: Social Science & Medicine. Vol. 258, article № 113101.
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WU, Zunyou; MCGOOGAN, Jennifer. 2020. “Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention” In: JAMA. Vol. 13, No. 323, pp. 1239-1242.
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ZHAO, Shi; LIN, Qianyi; RAN, Jinjun; MUSA, Sahilu; YANG, Guangpu; WANG, Weiming; LOU, Yijun; GAO, Daoz; YANG, Lin; HE, Daihai; WANG, Maggie. 2020. “Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak” In: International journal of infectious diseases: IJID: official publication of the International Society for Infectious Diseases. No. 92. pp 214-217.
AL-RAEEI, Marwan. 2020. “Te forecasting of COVID-19 with mortality using SIRD epidemic model for the United States, Russia, China, and the Syrian Arab Republic” In: AIP Advances. Vol. 10, No. 6, pp. 70-82.
ANASTASSOPOULOU, Cleo; RUSSO, Lucia; TSAKRIS, Athanasios; SIETTOS, Constantinos. 2020. “Data-based analysis, modelling and forecasting of the COVID-19 outbreak” In: Plos One. Vol. 15, No. 3, pp. 114-123.
ARE, Stephen Olusegun; EKUM, Matthew Iwada. 2020. “COVID-19 pandemic data visualization with moment about midpoint: exploratory and expository analyses” In: Asian Journal Probability Statistics. Vol. 8, No. 4, pp. 15-37.
ARONOV, Iosif; MAKSIMOVA, Olga; GALKINA, Nataliia. 2020. “COVID-19 Highest Incidence Forecast in Russia Based on Regression Model” In: International Journal of Mathematical Engineering and Management Sciences. Vol. 5, No. 5, pp. 812-819.
BOLLINGER, Robert; RAY, Stuart. 2021. New Variants of Coronavirus: What You Should Know. Johns Hopkins Medicine. Available online. In: https://www.hopkinsmedicine.org/health/conditions-and-diseases/ coronavirus/a-new-strain-of-coronavirus-what-you-should-know. Date of consultation: 05/05/2021.
CHINTALAPUDI, Nalini; BATTINENI, Gopi; AMENTA, Francesco. 2020. “COVID-19 virus outbreak forecasting of registered and recovered cases after sixty day lockdown in Italy: A data driven model approach” In: Journal of Microbiology Immunology and Infection. Vol. 53, No. 3, pp. 396-403.
CHUDIK, Alexander; MOHADDES, Kamiar; PESARAN, Hashem; RAISSI, Mehdi; REBUCCI, Alessandro. 2020. Economic consequencies of COVID-19: A counterfactual multi-country analysis. Research-based policy analysis and commentary from leading economists. Available online. In: https://voxeu.org/article/economic-consequences-covid-19- multi-country-analysis. Date of consultation: 05/05/2021.
DRAPKINA, Oksana; SAMORODSKAYA, Irina; SIVTSEVA,Marina; KAKORINA, Ekaterina; BRIKO, Nikolay; CHERKASOV, Sergey; ZINSERLING, Vsevolod; MALKOV, Pavel. 2020. “COVID-19: urgent questions for estimating morbidity, prevalence, case fatality rate and mortality rate” In: Cardiovascular Terapy and Prevention. Vol. 19, No. 3, article №2585.
FEDERAL STATE STATISTICS SERVICE OF RUSSIA. 2021. Statistical Dashboard. Available online. In: https://showdata.gks.ru/finder/. Date of consultation: 05/05/2021.
FERGUSON, Neil; LAYDON, Daniel; NEDJATI-GILANI, Gemma; IMAI, Natsuko; AINSLIE, Kylie. 2020. Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. Imperial College COVID-19 Response Team. Available online. In: https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/ covid-19/report-9-impact-of-npis-on-covid-19/. Date of consultation: 05/05/2021.
FERRARO, Ottavia Eleonora; PUCI, Mariangela Valentina; MONTOMOLI, Cristina; ROLESU, Sandro; CAPPAI, Stefano; LOI, Federica. 2020. “Official Data and Analytical Forecasts: Diferences and Similarities Among Coronavirus Disease (COVID-19)” In: Frontiers in Medicine. No. 7, No. 239, pp. 363-382.
GAO, Yuanyuan; ZHANG, Zuqin; YAO, Wei; YING, Qi; LONG, Chen; FU, Xinmiao. 2020. “Forecasting the cumulative number of COVID-19 deaths in China: a Boltzmann function-based modeling study” In: Infection Control and Hospital Epidemiology. Vol. 41, No. 7, pp. 841-843.
GERLI, Alberto; CENTANNI, Stefano; MIOZZO, Monica; VIRCHOW, Chistian; SOTGIU, Giovanni; CANONICA, Walter; SORIANO, Joan. 2020. “COVID-19 mortality rates in the European Union, Switzerland, and the UK: effect of timeliness, lockdown rigidity, and population density” In: Minerva medica. Vol. 111, No. 4, pp. 308-314.
HUANG, Chaolin; WANG, Yemin; LI, Xingwang; REN, Lili; ZHAO, Jianping; HU, Yi. 2020. “Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China” In: The Lancet. Vol. 395, No. 10223, pp. 497-506.
ILUNO, Christiana; TAYLOR, Jimoh; AKINMOLADUN, Olusegun; ADERELE, Oluwaseun; EKUM, Matthew. 2021. “Modelling the effect of Covid-19 mortality on the economy of Nigeria” In: Research in Globalization. Vol. 3, No. 100050, pp. 1200-1242.
IVANAJ, Ernest; OUKHALLOU, Youssef. 2020. The Economic and Institutional Determinants of COVID-19 Mortality. Munich Personal RePEc Archive. Available online. In: https://mpra.ub.uni-muenchen.de/103895/. Date of consultation: 05/05/2021.
KOBAK, Dmitry. 2021. “Excess mortality reveals Covid’s true toll in Russia” Significance. Vol. 18, No. 1, pp. 16-19.
LI, Qun; GUAN, Xuhua; WU, Peng; WANG, Xiaoye; ZHOU, Lei; TONG, Yeqing. 2020. “Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia” In: The New England Journal of Medicine. No. 382, pp. 1199-1207.
LIFSHITS, Marina; NEKLYUDOVA, Natalia. 2020. “COVID-19 mortality rate in Russian regions: forecasts and reality” In: R-economy. Vol. 6, No. 3, pp. 171-182.
LIU, Yin; GAYLE, Albert A; WILDER-SMITH, Annelies; ROCKLÖV, Joacim. 2020. “The reproductive number of COVID-19 is higher compared to SARS coronavirus” In: Journal of Travel Medicine. Vol. 27, No. 2, pp. 06-19.
MIDDELBURG, Rutger A; ROSENDAAL, Frits. 2020. “COVID-19: How to make between-country comparisons” In: International Journal of Infectious Diseases. Vol. 96, pp. 477-481.
NUSRATULLIN, Ilmir; KUZNETSOVA, Svetlana; GAZIZYANOVA, Yuliya; KUTSENKO, Ekaterina; BEREZHNAYA, Lubov. 2020. “Socio-economic development of Russia in terms of the BRICS countries’ development” In: Amazonia Investiga. Vol. 9, No. 27, pp. 52-61.
NUSRATULLIN, Ilmir; MROCHKOVSKIY, Nikolay; YARULLIN, Raul; ZAMYATINA, Natalia; SOLNTSEVA, Oksana. 2021. The “Financial Implications of the Coronavirus COVID-19 Pandemic: A Review” In: Cuestiones Politicas. Vol. 39, No. 68, pp. 325-342.
ONDER, Graziano; REZZA, Giovanni; BRUSAFERRO, Silvio. 2020. “Case- Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy” In: Jama-Journal of the American Medical Association. Vol. 323, No. 18, pp. 1775-1776.
ORAN, Daniel; TOPOL, Eric. 2020. “Prevalence of Asymptomatic SARS-CoV-2 Infection: A Narrative Review” In: Annals of internal medicine. Vol. 173, No. 5, pp. 362-367.
POLIDORI, Cristina; SIES, Helmut; FERRUCCI, Luigi; BENZING, Thomas. 2021. “COVID-19 mortality as a fingerprint of biological age” In: Ageing Research Reviews. Vol. 67, article №101308.
READ, Jonathan; BRIDGEN, Jessica; CUMMINGS, Derek; HO, Antonio; JEWELL, Chirs. 2021. “Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates” In: Philosophical Transactions B. Vol. 376, No. 20200265.
RYAZANTSEV, Sergey; IVANOVA, Alla; ARKHANGELSKY, Vladimir. 2021. “Increasing Depopulation in Russia in the Context of the Covid-19 Pandemic: Regional Features” In: Bulletin of the South-Russian State Technical University (NPI) Series Socio-Economic Sciences. Vol. 14, No. 2, pp. 7-20.
SÁNCHEZ-VILLEGAS, Pablo; CODINA, Antonio Daponte. 2020. “Modelos predictivos de la epidemia de COVID-19 en España con curvas de Gompertz. Gaceta Sanitaria” In: Press. Vol. 35, No. 6, pp. 263-290.
SEBASTIANI, Giovanny; MASSA, Marco; RIBOLI, Elio. 2020. “Covid-19 epidemic in Italy: evolution, projections and impact of government measures” In: European Journal of Epidemiology. Vol. 4, No. 35, pp. 341-345.
SEMENOVA, Yuliya; GLUSHKOVA, Natalya; PIVINA, Lyudmila; KHISMETOVA, Zaituna; ZHUNUSSOV, Yersin; SANDYBAEV, Marat; IVANKOV, Alexandr. 2020. “Epidemiological Characteristics and Forecast of COVID-19 Outbreak in the Republic of Kazakhstan” In: Journal of Korean Medical Science. Vol. 35, No. 24, pp. 45-56.
SHOJAEE, Sajad; POURHOSEINGHOLI, Mohamad Amin; ASHTARI, Sara; VAHEDIAN-AZIMI, Amir; ASADZADEH-AGHDAEI, Hamid; ZALI, Mohammad Reza. 2020. “Predicting the mortality due to Covid-19 by the next month for Italy, Iran and South Korea; a simulation study” In: Gastroenterology and hepatology from bed to bench. Vol. 13, No. 2. pp 177-179.
SORNETTE, Didier; MEARNS, Euan; SCHATZ, Michael; WU, Ke; DARCET, Didier. 2020. Interpreting, analysing and modelling COVID-19 mortality data. Nonlinear dynamics, 1–26. Available online. In: https://doi. org/10.1007/s11071-020-05966-z. Date of consultation: 05/05/2021.
STAROSTINA, Julia; TKACHEV, Ivan. 2021. Rosstat named the number of deceased Russians with COVID-19 in 2020. Available online. In: https:// www.rbc.ru/economics/08/02/2021/602132e19a7947073f7ddeb5. Date of consultation: 05/05/2021.
TANG, Biao; WANG, Xia; LI, Qian; BRAGAZZI, Nicola Luigi; TANG, Sanyi; XIAO, Yanni; WU, Jianhong. 2020. “Estimation of the Transmission Risk of the 2019-nCoV and Its Implication for Public Health Interventions” In: Journal of clinical medicine. Vol. 9, No. 2, pp. 462-479.
UNITED NATIONS. 2020. World Economic Situation and Prospects 2021. Available online. In: https://www.un.org/development/desa/dpad/ publication/world-economic-situation-and-prospects-2021/. Date of consultation: 05/05/2021.
VANDOROS, Sotiris. 2020. “Excess mortality during the Covid-19 pandemic: Early evidence from England and Wales” In: Social Science & Medicine. Vol. 258, article № 113101.
WORLD HEALTH ORGANIZATION. 2021. WHO Coronavirus (COVID-19) Dashboard. Available online. In: https://covid19.who.int/. Date of consultation: 05/05/2021.
WU, Zunyou; MCGOOGAN, Jennifer. 2020. “Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention” In: JAMA. Vol. 13, No. 323, pp. 1239-1242.
YANG, Shu; CAO, Peihua; DU, Peipei; WU, Ziting; ZHUANG, Zian; YANG, Lin; YU, Xuan; ZHOU, Qi; FENG, Xixi; WANG, Xiaohui; LI, Weiguo; LIU, Enmei; CHEN, Ju; CHEN, Yaolong; HE, Daihai. 2020. “Early estimation of the case fatality rate of COVID-19 in mainland China: a data-driven analysis” In: Annals of translational medicine. Vol. 8, No. 4, pp. 128-140.
ZHAO, Shi; LIN, Qianyi; RAN, Jinjun; MUSA, Sahilu; YANG, Guangpu; WANG, Weiming; LOU, Yijun; GAO, Daoz; YANG, Lin; HE, Daihai; WANG, Maggie. 2020. “Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak” In: International journal of infectious diseases: IJID: official publication of the International Society for Infectious Diseases. No. 92. pp 214-217.
Published
2021-12-24
How to Cite
Nusratullin, I., Drozdov, I., Ermakov, A., Koksharova, E., & Mashchenko, M. (2021). Movimiento de población natural y COVID-19: datos de Rusia. Political Questions, 39(71), 986-1007. https://doi.org/10.46398/cuestpol.3971.60
Section
Derecho Público
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