CHARACTERISTICS OF DEMOGRAPHIC RESILIENCE OF THE POPULATION IN UKRAINE DURING THE PANDEMIC OF COVID-19

Abstract

The full-scale military invasion of Ukraine by the Russian Federation came at a time when our country had been weakened by a series of shocks in a relatively short historical period. Shocks such as a prolonged pandemic and war can disrupt and, in some cases, halt demographic development. In this context, the study of demographic resilience on the eve of a full-scale war, which became a new powerful shock for Ukraine, is relevant and necessary. The complexity of this issue does not allow us to provide all the answers in one article. The purpose of our paper is to determine the main parameters of the demographic resilience of the population of Ukraine in the Covid-19 period and to compare them with the characteristics of resilience in other periods of the greatest shocks experienced by our country, as well as with the indicators of other countries. In our study the main indicators of transient dynamics (convergence time, reactivity, population inertia, damping ratio) were calculated for the first time for the population of Ukraine. The influence of the contribution of different age groups of women to total fertility on the age structure of the population (with the same total fertility rate) was also determined for the first time. The calculations were based on the stable population model, the Leslie matrix, fertility tables, and life tables. The resilience indicators were calculated using the popdemo package. Methods of comparison, generalisation, and analogy were also used. Among the characteristics of demographic resilience, the half-life indicator stands out for its simplicity of calculation and interpretation. In Ukraine, the halving time for the population is decreasing, but it is still higher for the real population than for its stable equivalent. The age structure of the real population, formed under more favourable conditions, mitigates the negative consequences of shock periods, but the long-term preservation of the current regime of mortality and fertility will inevitably worsen the characteristics of the population. In Ukraine, advanced motherhood is an element of the adaptive cycle and requires a rethinking of its meaning and role, as it can be one of the internal mechanisms aimed at the resilience of the system in shock periods. In the conditions of the lowest-low fertility and mortality regime in Ukraine in 2021, advanced maternal age contributed to some increase in the number of births and a certain rejuvenation of the age structure of the population.

REFERENCES

1. Holling, C.S. (1973). Resilience and Stability of Ecological Systems. Annual Review of Ecology and Systematics, 4, 1—23. https://doi.org/10.1146/annurev.es.04.110173.000245
2. Walker, B., Holling, C.S., Carpenter, S.R., & Kinzig, A. (2004). Resilience, adaptability and transformability in social–ecological Ecology and Society, 9(2), 1—9. https://doi.org/10.5751/ES-00650-090205
3. Holling, C.S. (1996). Engineering resilience versus ecological resilience. In P.C. Schulze, editor. Engineering within ecological constraints. Washington, DC: The National Academies Press, 31—43. https://doi.org/10.17226/4919
4. Dakos, V., & Kéfi, S. (2022). Ecological resilience: what to measure and how. Environmental Research Letters, 17(4), 1—22. https://doi.org/10.10 88/1748-9326/ac5767
5. Holling, C.S. (2001). Understanding the Complexity of Economic, Ecological, and Social Systems. Ecosystems, 4(5), 390—405. https://doi.org/10.1007/s10021-001- 0101-5
6. Pimm, S., & Lawton, J. (1977). Number of trophic levels in ecological communities. Nature, 268( 5618), 329—331. https://doi.org/10.1038/268329a0
7. Dakos, V., & Bascompte, J. (2014). Critical slowing down as early warning for the onset of collapse in mutualistic communities. Proceedings of the National Academy of Sciences, 111(49), 17546—17551. https://doi.org/10.1073/pnas.1406326111 
8. Carpenter, S.R., Cole, J.J., Pace, M.L., Batt, R., & Brock, W.A. et al. (2011). Early warnings of regime shifts: a whole-ecosystem experiment. Science, 332(6033), 1079—1082. https:// doi.org/10.1126/science.1203672
9. Quinlan, A.E., Berbes-Blazquez, M., Haider, L.J., & Peterson, G.D. (2016). Measuring and assessing resilience: broadening under standing through multiple disciplinary perspectives. Journal of Applied Ecology, 53(3), 677—687. https://doi.org/10.1111/1365-2664.12550
10. Pyrozhkov, S.I., Bozhok, Ye.V., & Khamitov, N.V. (2021). National Resilience of the Country: Strategy and Tactics of Anticipation of Hybrid Threats. Visnyk of the National Academy of Sciences of Ukraine, 8, 74—82. https://doi.org/10.15407/visn2021.08.074 [in Ukrainian]
11. Colantoni, A., Halbac-Cotoara-Zamfir, R., Halbac-Cotoara-Zamfir, C., Cudlin, P., Salvati, L., & Gimenez Morera, A. (2020). Demographic Resilience in Local Systems: An Empirical Approach with Census Data. Systems, 8(3), 1—17. https://doi.org/10.3390/ systems8030034
12. Cecchini, M., Cividino, S., Turco, R., & Salvati, L. (2019). Population Age Structure, Complex Socio-Demographic Systems and Resilience Potential: A Spatio-Temporal, Evenness-Based Approach. Sustainability, 11(7), 1—12. https://doi.org/10.3390/su11072050
13. Heckbert, S., Costanza, R., & Parrott, L. (2014). Achieving sustainable societies: lessons from modelling the ancient Maya. Solutions, 5, 55—64. https://www.researchgate.net/ publication/277077643
14. Pimm, S.L., Donohue, I., Montoya, J. M., & Loreau, M. (2019). Measuring resilience is essential to understand it. Nature Sustainability, 2(10), 895—897. https://doi.org/10.1038/ s41893-019-0399-7
15. Capdevila, P., Stott, I., Beger, M., & Salguero-Gómez, R. (2020). Towards a Comparative Framework of Demographic Resilience. Trends in Ecology & Evolution, 35(9), 776—786. https://doi.org/10.1016/j.tree.2020.05.001
16. Stott, I., Townley, S., & Hodgson, D. (2011). A framework for studying transient dynamics of population projection matrix models. Ecology Letters, 14(9), 959—970. https://doi. org/10.1111/j.1461-0248.2011.01659.x
17. Neubert, M.G., & Caswell, H. (1997). Alternatives to Resilience for Measuring the Responses of Ecological Systems to Perturbations. Ecology, 78(3), 653—665. https://doi.org/10.1890/0012-9658(1997)078[0653:ATRFMT]2.0.CO;2
18. Keyfitz, N., & Caswell, H. (2005). Applied mathematical demography. 3rd edition. Springer. https://doi.org/10.1007/b139042
19. Caswell, H., & Neubert, M.G. (2005). Reactivity and transient dynamics of discrete-time ecological systems. Journal of Difference Equations and Applications, 11(4—5), 295—310. https://doi.org/10.1080/10236190412331335382
20. Stott, I., Hodgson, D., & Townley, S. (2012). popdemo: an R package for population demography using projection matrix analysis. Methods in Ecology and Evolution, 3(5), 797—802. https://doi.org/10.1111/j.2041-210X.2012.00222.x
21. United Nations, Department of Economic and Social Affairs, Population Division (2022). World Population Prospects 2022, Online Edition.
22. Statistical handbook «Fertility tables and life tables» https://www.ukrstat.gov.ua/druk/ publicat/kat_u/publnasel_u.htm [in Ukrainian].
23. Pyrozhkov, S.I. (2008). Selected scientific essays in 2 vols. Vol. 1: Demographic and labour potential. Kyiv. [in Ukrainian].
24. Aksyonova, S.Yu. (2019). The Relation of The Mean Age of Women at Childbearing and Fertility Rate. Demography and Social Economy, 36(2), 23—38. https://doi.org/10.15407/ dse2019.02.023 [in Ukrainian].
25. Korchak-Chepurkivskyi, Y.O. (1970). Calculation of the growth rate of the number and age composition of those living in a stabilised population with a constant level of migration. (on the example of Kyiv). Demographic studies, 1, 24—41 [in Ukrainian].
26. Kenny, L.C., Lavender, T., McNamee, R., O’Neill, S.M., Mills, T., & Khashan, A.S. (2013). Advanced Maternal Age and Adverse Pregnancy Outcome: Evidence from a Large Contemporary Cohort. PLoS One, 8(2):e56583. https://doi.org/10.1371/journal.pone. 0056583