THE IMPACT OF COVID-19 ON MORTALITY AND LIFE EXPECTANCY IN UKRAINE IN 2020-2021

Abstract

With the increasing intensity of movement of people between countries and continents, humanity has become more vulnerable to the spread of diseases on a global scale. The rapid spread of COVID-19 in 2020 has led to a significant shift in the mortality structure of the population and tangible losses in average life expectancy. Governments of different countries have responded differently to this challenge. Therefore, it is relevant to compare the experience of Ukraine against the other countries. The purpose of this article is to analyze and quantify the impact of COVID-19 on mortality and life expectancy in Ukraine. The novelty is an estimate of the impact of COVID-19 on mortality in Ukraine by different methods based on the data for the complete years 2020-2021. Methods of calculation and analysis of demographic indicators, life tables, graphic method, decomposition method, and Lee—Carter method were used. The existing definitions of excess mortality are analyzed. Based on the use of 6 methods it is determined that the pandemic led to an increase in the number of deaths in Ukraine (without Donbas and Crimea) from 92.7 to 241.5 thousand. Most estimates fall into the range of 147.5-224.2 thousand. It is shown that the biggest number of excess deaths is observed in older age groups, especially 65-84 years. The highest loss of life potential occurred in the 65-74 age group. In 2020-2021, life expectancy at birth for women decreased by 2.62 years, while for men the reduction was 1.77 years. The increase in mortality from COVID-19 resulted in a loss of 1.91 and 1.51 years, respectively. In 2020-2021, a sharp increase in mortality from respiratory diseases was recorded. It is shown that mortality from this class of diseases has a direct strong (correlation coefficient 0.91) and significant (p< 0.001) correlation with mortality from COVID-19. The relationship between these causes of death is supported by a similar effect on the age pattern of life expectancy losses. The increase in the overall male mortality rate was significantly mitigated by decrease in mortality from infectious and parasitic diseases, as well as external causes of death. Women, due to their much lower mortality rates from these classes of causes, have a markedly lower potential for improvement in this area. Therefore, it is necessary to expand and facilitate access to professional medical care and not limit it, as was done during lockdowns and quarantines.

1. Beaney, T., Clarke, J. M., & Jain, V. et al. (2020). Excess mortality: the gold standard in measuring the impact of COVID-19 worldwide? Journal of the Royal Society of Medicine. 113(9), 329-334. https://doi:10.1177/0141076820956802
2. Riffe, T., & Acosta, E. (2021). Data Resource Profile: COVerAGE-DB: a global demographic database of COVID-19 cases and deaths. International Journal of Epidemiology, 50, 2, 390-390f. https://doi:10.1093/ije/dyab027
3. Modig, K., Ahlbom, A., & Ebeling, M. (2021). Excess mortality from COVID-19: weekly excess death rates by age and sex for Sweden and its most affected region. The European Journal of Public Health, 31, 1, 17-22. https://doi:10.1093/eurpub/ckaa218
4. Dudel, C., Riffe, T., & Acosta, E. et al. (2020). Monitoring trends and differences in COVID-19 case-fatality rates using decomposition methods: contributions of age structure and agespecific fatality. PLoS One, 15(9), 1-11. https://doi:10.1371/journal.pone.0238904
5. Karlinsky, A., & Kobak, D. (2021). Tracking excess mortality across countries during the COVID-19 pandemic with the world mortality dataset. ELife, 1-21. https://doi:10.7554/ eLife.69336
6. Wang, H. et al. (2022). Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020-21. The Lancet, 1-24. https://doi: 10.1016/S0140-6736(21)02796-3
7. Islam, N., Jdanov, D., & Shkolnikov, V. et al. (2021). Effects of covid-19 pandemic on life expectancy and premature mortality in 2020: time series analysis in 37 countries. BMJ, 1-14. https://doi:10.1136/bmj-2021-066768
8. Lee, R. D., & Carter, L. R. (1992). Modeling and forecasting US mortality. Journal of the American Statistical Association, 87, 419, 659-671. https://doi:10.2307/2290201
9. Jdanov, D., Galarza, A., & Shkolnikov, V. et al. (2021). The short-term mortality fluctuation data series, monitoring mortality shocks across time and space. Scientific Data, 8, 235, 1-8. https://doi:10.1038/s41597-021-01019-1
10. Aburto, J. M., Tilstra, A. M., Floridi, G., & Dowd, J. B. (2022). Significant impacts of the COVID-19 pandemic on race/ethnic differences in USA mortality. medArxiv. 28 p. https://doi:10.1101/2022.04.04.22273385
11. Aburto, J. M., Schöley, J., & Kashnitsky, I. et al. (2022). Quantifying impacts of the COVID-19 pandemic through life expectancy losses: a population level study of 29 countries. International Journal of Epidemiology, 51, 1, 63-74. https://doi:10.1093/ije/dyab207
12. Aburto, J. M., Kashyap, R., & Schöley, J. et al. (2021). Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis. Journal of Epidemiology and Community Health, 75, 735-40. https://doi:10.1136/jech-2020-215505
13. Overview of the COVID-19 pandemic development in Ukraine (2022). https://www.nas. gov.ua/UA/Messages/Pages/View.aspx?MessageID=9007 [in Ukrainian].
14. Glossary: Excess mortality (2022). https://ec.europa.eu/eurostat/statistics-explained/index. php?title=Glossary:Excess_mortality
15. Chiang, C. L. (1984). Life Table and Its Applications. Malabar, Florida: Robert E. Krieger Publishing Company. 316 p.
16. Andreev, E. (1982). The Method of Components in the Analysis of Length of Life. Bulletin of Statistics, 9, 42-47 [in Russian].
17. Hyndman, R. J., with contributions from H. Booth, L. Tickle, J. Maindonald (2019). Package demography: forecasting mortality, fertility, migration and population data. R package, Version 1.22.
18. Human Mortality Database. Short-term Mortality Fluctuations. Visualization Toolkit (2022). https://mpidr.shinyapps.io/stmortality/
19. Shkolnikov, V. M., Klimkin, I., & McKee, M. et al. (2022). What should be the baseline when calculating excess mortality? New approaches suggest that we have underestimated the impact of the COVID-19 pandemic and previous winter peaks. SSM-Population Health, 18, 1-13. https://doi:10.1016/j.ssmph.2022.101118
20. Population and Social Statistics. Number of Deaths by Causes of Death (2022). https:// ukrstat.gov.ua
21. Hiam, L. et al. (2018). Why is life expectancy in England and Wales ‘stalling’? Journal of Epidemiology and Community Health, 72, 404-408. https:// doi: 10.1136/jech-2017-210401
22. Me hta, N. K., Abrams, L. R., & Myrskylä, M. (2020). US life expectancy stalls due to cardiovascular disease, not drug deaths. Proceedings of the National Academy of Sciences, 117, 13, 6998-7000. https://doi:10.1073/pnas.1920391117
23. Ho, J. Y., & Hendi, A. S. (2018). Recent trends in life expectancy across high income countries: retrospective observational study. BMJ, 362, 1-14. https:// doi: 10.1136/bmj.k2562
24. Hia m, L., & Dorling, D. (2022). The end of great expectations? BMJ, 377, 1-3. https://doi: 10.1136/bmj-2022-071329
25. Ren , J., Pang, W., Luo, Y., & Cheng, D. et at. (2022). Impact of Allergic Rhinitis and Asthma on COVID-19 Infection, Hospitalization, and Mortality. The Journal of Allergy and Clinical Immunology: In Practice, 10, 1, 124-133. https://doi:10.1016/j.jaip. 2021.10.049
26. Loh ia, P., Sreeram, K., Nguyen, P., Choudhary, A., Khicher, S., Yarandi, H., Kapur, S., & Badr, M. S. (2021). Preexisting respiratory diseases and clinical outcomes in COVID-19: a multihospital cohort study on predominantly African American population. Respiratory Research, 22, 37, 1-9. https://doi:10.1186/s12931-021-01647-6
27. Ave yard, P., Gao, M., Lindson, N., Hartmann-Boyce J., & Watkinson, P. et al. (2021). Association between pre-existing respiratory disease and its treatment, and severe COVID-19: a population cohort study. The Lancet. Respiratory Medicine, 9, 909-923. https://doi:10.1016/S2213-2600(21)00095-3
28. Čelutkienė, J., Čerlinskaitė-Bajorė, K., & Bajoras, V. et al. (2022). Collateral effect of the COVID-19 pandemic on cardiology service provision and cardiovascular mortality in a population-based study: COVID-COR-LT. Clinical Research in Cardiology, 1-17. https:// doi:10.1007/s00392-022-02033-y
29. Zeymer, U., Ahmadli, V., & Schneider, S. et al. (2022). Effects of the COVID-19 pandemic on acute coronary syndromes in Germany during the first wave: the COVID-19 collateral damage study. Clinical Research in Cardiology, 1-11. https://doi:10.1007/s00392-022- 02082-3
30. Brant, L ., Pinheiro, P., Ribeiro, A., & Machado, I. et al. (2022). Cardiovascular Mortality During the COVID-19 Pandemics in a Large Brazilian City: A Comprehensive Analysis. Global Heart, 17(1):11. https://doi:10.5334/gh.1101