Optimisation of socio-economic, environmental and public health determinants of national security for post-pandemic recovery

Размещено на http://allbest.ru

1Pan-European University

2Sumy State University

Optimisation of socio-economic, environmental and public health determinants of national security for post-pandemic recovery

1Jana Firstova,

2Alina Vysochyna,

The Czech Republic

Ukraine



Abstract

The COVID-19 pandemic became a significant test for social and economic stability worldwide. Its destructive effect forces authorities to overcome negative impacts and ensure socio-economic recovery. The research distinguishes socio-economic, environmental and public health determinants of national security before and after the pandemic.

The post-pandemic recovery strategy covers various perspectives: urban, tourism, employment, healthcare, economic recovery; sustainable development; innovations and investments; environment protection; social and psychological support. We develop the National Security Index. It comprises 16 indicators of economic, environmental and social proxies of national security. The Index concerns 34 European countries in 2000-2022. Several methods were applied.

Firstly, the natural and Savage normalisation (to bring indicators to a comparable form).

Secondly, the principal component analysis, the Fishburn formula and ranking (to define the significance of indicators).

Thirdly, the additive-multiplicative convolution (to integrate individual parameters).

The National Security Index showed a delayed CO VID-19 destructive impact (in 2020 the Index decreased in 2 out of 34 countries). Negative trends of the pandemic revealed actively in 2021 (the Index decreased in 14 out of 34 countries) and became dramatical in 2022 (the Index decreased in 28 out of 34 countries).

Factor analysis showed that national security improvement in 2019, 2020 and 2022 mostly depended on 3-4 determinants while 6 determinants became especially crucial for the national security in 2021. Summarising the results, we can single out a range of important steps to achieve the post-pandemic recovery in national security. Economic measure might be focused on overcoming inflation, government expenditures, optimisation and maintenance of the socio-economic resilience by increase of total reserves in months of imports. Environmental measures consist in strengthening energy independence (reduction of energy production and distribution losses, fall of greenhouse gas emissions). Social measures are simulating employment. The regression analysis findings confirm no statistically significant impact of public health determinants on national security in 2019-2022.

Keywords: state national security; coronavirus disease; COVID-19; post-pandemic recovery; resilience of the socio-economic system; public health



Аннотация

Оптимизация социально-экономических, экологических и медико-санитарных факторов, определяющих национальную безопасность, для постпандемического восстановления

Пандемия COVID-19 стала серьезным испытанием для социальной и экономической стабильности во всем мире. Ее разрушительное воздействие вынуждает власти преодолевать негативные последствия и обеспечивать социально-экономическое восстановление.

В исследовании выделяются социально-экономические, экологические и медицинские факторы, определяющие национальную безопасность до и после пандемии. Стратегия восстановления после пандемии охватывает различные аспекты: городское хозяйство, туризм, занятость, здравоохранение, восстановление экономики; устойчивое развитие; инновации и инвестиции; охрана окружающей среды; социальная и психологическая поддержка. Мы разрабатываем Индекс национальной безопасности. Он включает в себя 16 показателей экономической, экологической и социальной составляющей национальной безопасности. Индекс охватывает 34 европейские страны в 2000-2022 годах. Было применено несколько методов.

Во-первых, естественная и упрощенная нормализация (для приведения показателей к сопоставимому виду).

Во-вторых, анализ главных компонент, формула Фишберна и ранжирование (для определения значимости показателей).

В-третьих, аддитивно-мультипликативная свертка (для интегрирования отдельных параметров).

Индекс национальной безопасности продемонстрировал замедленное деструктивное воздействие (в 2020 году индекс снизился в 2 из 34 стран). Негативные тенденции пандемии активно проявились в 2021 году (показатель снизился в 14 из 34 стран) и приобрели драматический характер в 2022 году (показатель снизился в 28 из 34 стран). Факторный анализ показал, что улучшение национальной безопасности в 2019, 2020 и 2022 годах в основном зависело от 3-4 детерминант, в то время как 6 детерминант стали особенно важными для национальной безопасности в 2021 году.

Подводя итоги, мы можем выделить ряд важных шагов для достижения постпандемического восстановления национальной безопасности. Экономические меры могут быть направлены на преодоление инфляции, сокращение государственных расходов, оптимизацию и поддержание социально-экономической устойчивости путем увеличения общих резервов в месяцах импорта.

Экологические меры заключаются в укреплении энергетической независимости (сокращение потерь при производстве и распределении энергии, сокращение выбросов парниковых газов). Социальные меры имитируют занятость. Результаты регрессионного анализа подтверждают отсутствие статистически значимого влияния детерминант общественного здравоохранения на национальную безопасность в 2019-2022 гг.

Ключевые слова: национальная безопасность государства; коронавирусная болезнь; COVID-19; постпандемическое восстановление; устойчивость социально-экономической системы; общественное здравоохранение



Introduction

Intensified globalisation and integration lead to a radical transformation of socio-economic relations on national and supranational levels. It is realised in new ways of cooperation and development, interdependence between countries and quick dissemination of destructive processes. On the one hand, globalisation reduces the cost of manufacturing goods or providing services. It also optimises business processes, upgrades technologies and innovations, etc. On the other hand, close relations between countries and economic agents significantly raise risks of large-scale crisis in a certain country. These mechanisms took place during the global financial crisis of 2007-2009 and COVID-19. They go on due to wartime combats in Ukraine. Therefore, it is critically important to have a clear understanding of patterns in determinants' contribution to state national security because this can reveal the channels to eliminate the impact of destructive processes.

Meanwhile, state national security is a complex phenomenon with economic, social and environmental proxies. Many its components were negatively affected during the COVID-19 pandemic, but the scale and strength of this impact differ significantly. Additionally, for some components of state national security, the negative pandemic impact manifested itself immediately while for others this action was delayed in time (Vysochyna et al, 2023). Within lockdowns and manufacture reduction, even improvement of certain indicators was recorded, e.g. environment protection (Hammad et al., 2023). Along with distinguished temporal patterns of the impact force and direction caused by the pandemic on state national secu rity, we should consider synergistic and transmission processes between separate elements of state national security. In particular, the positive state intervention aimed at post-pandemic recovery can be neutralised due to explicit and latent relationships between elements and parameter of state national security.

Thus, we need to define the most effective and fast mechanisms of post-pandemic recovery in state national security. Firstly, we will identify those components of national security that were most vulnerable to the destructive COVID-19 impact. Secondly, we will establish the most relevant determinants of the state national security resilience. Determining these parameters will allow solving several important tasks. On the one hand, we will find the main security elements to overcome the COVID-19 destructive effects. On the other hand, we will establish the most efficient tools for post-pandemic recovery. Solution of these tasks will become a basis for identifying the optimal combinations and target values of financial, socio-economic, environmental, and public health determinants. They might help to recover national security after COVID-19.

The research is going to identify theoretical and empirical patterns for distinguishing the significance of financial, socio-economic, environmental and public health determinants of national security in pandemic and pre-pandemic periods. Theoretical generalisation is conducted based on the bibliometric analysis (VOSviewer, 2024). Empirical part of the research considers using principal component analysis and panel data regression (Stata, 2024). Theoretical and empirical findings determine the post-pandemic recovery goals and the most effective tools to achieve them.



Literature review

The first stage is to identify the most effective mechanisms and priority areas of post -pandemic recovery. We conducted a bibliometric analysis of 307 Scopus papers via VOSviewer (2024). The bibliometric analysis appeals to works where the phrase “post-pandemic recovery” is mentioned in titles, keywords or abstracts. Having risen to the pandemic in 2020, COVID-19 attracts publications of 2020-2024. The annual stock of such papers was: 2020 - 17; 2021 - 62; 2022 - 87; 2023 - 119; 2024 - 22.

The leading countries of this research are represented in Figure 1.

Figure 1. The TOP-10 countries with the largest amount of Scopus publications on the given topic Source: Based on Scopus (2024)

The most active in post-pandemic recovery studies are scientists from the UK, the USA, and China. Australia, Canada, and Italy follow. Instead, India, Indonesia, Germany, and North Africa finish the group. Consequently, there is a deep interest to post-pandemic recovery among researchers from different continents. economic pandemic medical national security

Figure 2 shows the relations between Scopus keywords in papers dedicated the post-pandemic recovery topic. The bibliometric analysis confirms the presence of three meaningful research clusters in post-pandemic recovery:

• Red cluster - research to aim urban, tourism, employment and healthcare recovery;

• Green cluster - research to provide economic and sustainable development, innovations and investments, environmental protection after COVID-19;

• Blue cluster - research to identify social and psychological determinants of post-pandemic recovery.

Figure 2. Network visualisation for co-occurrence of key words in Scopus publications on postpandemic recovery

Source: Based on VOSviewer (2024) and Scopus (2024)

The most cited Scopus publications are mentioned in Table 1.

Table 1. The TOP-10 most cited Scopus publications on post-pandemic recovery

№	Document title	Authors	Source	Year	Cited by
1	A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0	Ivanov, D. & Dolgui, A.	Production Planning and Control, 32(9), 775-788	2021	517
2	Social costs of tourism during the COVID-19 pandemic	Qiu, R.T.R. et al.	Annals of Tourism Research, 84, 102994	2020	390
3	Who loses income during the COVID-19 outbreak? Evidence from China	Qian, Y., Fan, W.	Research in Social Stratification and Mobility, 68, 100522	2020	132
4	The impact and implications of COVID-19: An Australian perspective	O'Sullivan, D. et al.	International Journal of Community and	2020	127
№	Document title	Authors	Source	Year	Cited by
5	Effects of COVID-19 on the Sustainable Development Goals (SDGs)	Shulla, K. et al.	Discover Sustainability, 2(1), 15	2021	124
6	Greening the post-pandemic recovery in the G20	Barbier, E.B.	Environmental and Resource Economics, 76(4), 685-703	2020	115
7	SARS-CoV-2 impact on elective orthopaedic surgery: Implications for postpandemic recovery	Jain, A. et al.	Journal of Bone and Joint Surgery, 102(13), E68	2020	102
8	Exiting the COVID-19 pandemic: After-shock risks and avoidance of disruption tails in supply chains	Ivanov, D.	Annals of Operations Research	2021	97
9	The Covid-19 pandemic and the accommodation sharing sector: Effects and prospects for recovery	Gerwe, O.	Technological Forecasting and Social Change, 167, 120733	2021	59
10	Climate mitigation scenarios with persistent COVID-19- related energy demand	Kikstra, J.S. et al.	Nature Energy, 6(12), 1114-1123	2021	48

Source: Based on Scopus (2024)

Considering the most cited papers on post-pandemic recovery, we see that all articles can be conditionally divided into several blocks. Firstly, publications about the positive pandemic impact on environment and climate change to ensure sustainable development.

Secondly, documents dealing with national-based peculiarities of post-pandemic recovery and its conditions. Thirdly, articles on the tourism role in post - pandemic recovery and its development features. Fourthly, papers on medical and physiological recovery after SARS-CoV-2.

The oldest publications dedicated to the post-pandemic recovery perspectives argued that innovations, digitalisation and technological adaptivity create the background for challenge triggered by COVID-19 (Fu et al., 2020; Fu, 2020; Novikova et al., 2021). Moreover, scientists claim that world community obliged to save positive environmental results from pandemic lockdowns and shortage of negative anthropogenic impact by promoting green component in recovery strategies (Chen et al., 2020; Le Billon et al., 2021). COVID-19 also triggers research of world transformation from globalisation to fragmentation (Abdal & Ferreira, 2021; Santiago et al., 2024).

Along with macroeconomic perspectives at the early stage of post-pandemic recovery research, scientists also pointed out huge importance of social inclusion and mental health support in post - pandemic world (Ioakimidis & Maglajlic, 2021; Berry, 2021).

The most recent publications on post-pandemic recovery focus on:

• Post-pandemic recovery of specific industries - catering (Jia et al., 2024), tourism and hospitality industry (Klarin et al., 2024; Gozzoli et al., 2024; Descultu Grigore et al., 2024; Carvalho & Camacho, 2023; Nguyen & Nguyen, 2023), ride-sharing industry (Cheng et al., 2024);

• Environmental impacts of post-pandemic recovery (Deng et al., 2024);

• Transformation of business operations in the post-pandemic era (Wei et al., 2024);

• New approaches of medical care and mental health protection after COVID-19 (Jackson et al., 2024; Dingle et al., 2024; Natalia & Syakurah, 2021; Gustafsson et al., 2023);

• Educational changes in the post-pandemic world (Arredondo-Trapero et al., 2024).

However, there is a lack of studies to substantiate socio-economic prerequisites of post-pandemic recovery. Besides, all publications tend to examine a single, narrow area of post-pandemic recovery. There is a need for generalisation and more comprehensive analysis in this area.



Methodology

Now, we are going to determine the most significant elements of state national security. It should be primarily targeted by state interventions within the post-pandemic recovery.

In a previous study (Vysochyna et al., 2023), we substantiated the choice of ecological and natural resources, economic and social parameters to quantify state national security. This list is given below:

• Annual freshwater withdrawals, total (% of internal resources) (Water);

• CO2 emissions (metric tons per capita) (CO2);

• Nitrous oxide emissions (thousand metric tons of CO2 equivalent) (NO2);

• Electric power consumption (kWh per capita) (Cons);

• Electricity production from renewable sources, excluding hydroelectric (% of total) (Ren_prod);

• Electric power transmission and distribution losses (% of output) (Loss);

• Employment to population ratio, 15+, total (%) (modeled ILO estimate) (Empty;

• Gini index (Gini);

• School enrollment, secondary (% gross) (School);

• GDP per capita (current US$) (GDP_pc);

• General government final consumption expenditure (% of GDP) (GGFCE);

• Gross capital formation (% of GDP) (GCF);

• Inflation, consumer prices (annual %) (Infl);

• Trade (% of GDP) (Trade);

• Total reserves in months of imports (Res);

• Military expenditure (% of GDP) (Mil_exp).

All statistical data are generated from open sources - the World Bank DataBank (2024). The study was implemented for a sample of 34 European countries (Albania, Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Moldova, the Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Serbia, the Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Ukraine, the United Kingdom). The time range is 2000-2022.

The algorithm to determine the composite indicator of state national security is also described in the previous paper (Vysochyna et al., 2023). In general, the algorithm provides for the sequential implementation of several stages:

• Converting the indicators for comparison (elimination of negative indicator values, normalisation via stimulating or inhibiting influence of indicators using natural and Savage normalisation);

• Appling the principal component analysis, the Fishburn formula and ranking to define significance of a separate indicator contribution to the integral one;

• Establishing the integral indicator of state national security via additive-multiplicative convolution.

We are going to identify patterns of distinguishing significance in financial, socio-economic and environmental components of state national security. The same concerns changes in their patterns for the pandemic and pre-pandemic periods. Therefore, the 2019-2022 significance parameters of state national security will be found through the principal component analysis. The parameter comparison will determine how COVID-19 affects the parameter significance in state national security.

To identify the influence of public health determinants on the National Security Index, we will conduct the regression analysis for relationships between the National Security Index and public health determinants in 2019-2022.

Results

Now, it is necessary to form a generalised index of state national security for 34 European countries for 2000-2022. The first stage of this approach, as indicated in the previous work (Vysochyna et al., 2023), is to bring indicators to a comparable form. As far as some national security proxies have negative values, the simplest normalisation techniques are not applicable. Thus, we should use the Savage normalisation for indicators-inhibitors (Water, CO2, NO2, Cons, Loss, Gini, Infl) and the natural normalisation for stimulatory indicators (Ren_prod, Empl, School, GDP_pc, GGFC, GCF, Mil exp, Trade, Res). This approach is described in properly in a previous work (Vasylieva et al., 2022). The parameters brought to a comparable form range from 0 to 1.

The next stage is applying the principal component analysis to determine significance of the individual indicator contribution to the integral one. Graphical and analytical results are presented in Figure 3 and Table 2, respectively.

Table 2. Results of the principal components analysis

Component	Eigenvalue	Difference	Proportion	Cumulative
Comp1	4.1016	2.0613	0.2563	0.2563
Comp2	2.0403	0.3664	0.1275	0.3839
Comp3	1.6739	0.4308	0.1046	0.4885
Comp4	1.2430	0.0433	0.0777	0.5662
Comp5	1.1997	0.2693	0.0750	0.6412
Comp6	0.9305	0.0770	0.0582	0.6993
Comp7	0.8535	0.1323	0.0533	0.7527
Comp8	0.7212	0.0863	0.0451	0.7977
Comp9	0.6349	0.0414	0.0397	0.8374
Comp10	0.5935	0.1364	0.0371	0.8745
Comp11	0.4570	0.0274	0.0286	0.9031
Comp12	0.4296	0.0784	0.0268	0.9299
Comp13	0.3512	0.0688	0.0219	0.9519
Comp14	0.2823	0.0167	0.0176	0.9695
Comp15	0.2656	0.0433	0.0166	0.9861
Comp16	0.2223	.	0.0139	1.0000

Notes: Comp 1-16 - principal component

Source: Authors' calculations in Stata 14.2/SE software (Stata, 2024)



Source: Authors' calculations in Stata 14.2/SE software (Stata, 2024)

Taking into account the data presented in Figure 3, the slope angle on the graph becomes gentler after the fourth principal component. However, a certain jump from the 5th to the 6th principal component and variation values of Table 2 make us choose not 4 but 6 principal components to develop the integral National Security Index.

Weighting coefficients are given in Table 3.

Table 3. Results of the weighting coefficients identification

Variable	Comp1	Comp2	Comp3	Comp4	Comp5	Comp6	Av.	Rank	Weight
Water	0.0469	0.1813	0.4391	0.1199	0.3487	0.2423	0.2297	7	0.0946
CO2	0.2595	0.1014	0.3400	0.0629	0.4151	0.0086	0.1979	4	0.0541
NO2	0.0655	0.4665	0.0163	0.2566	0.3103	0.3706	0.2476	8	0.1081
Cons	0.2982	0.1439	0.3718	0.2429	0.0252	0.0186	0.1834	3	0.0405
Ren prod	0.2814	0.0048	0.1593	0.2308	0.4766	0.1361	0.2148	6	0.0811
Loss	0.3673	0.1370	0.0416	0.0627	0.2566	0.1035	0.1615	1	0.0135
Empl	0.3515	0.1960	0.1224	0.1281	0.1429	0.4027	0.2239	7	0.0946
Ginny	0.2871	0.1241	0.1546	0.3324	0.085	0.2608	0.2073	5	0.0676
School	0.3537	0.0237	0.1343	0.1226	0.3125	0.0336	0.1634	1	0.0135
GDP pc	0.3854	0.1300	0.1661	0.1146	0.0694	0.2034	0.1782	2	0.0270
GGFC E	0.2709	0.3094	0.0234	0.2815	0.2234	0.3902	0.2498	8	0.1081
GCF	0.0898	0.4459	0.1917	0.0701	0.2883	0.0374	0.1872	3	0.0405
Infl	0.1276	0.0821	0.0136	0.6023	0.1145	0.5700	0.2517	9	0.1216
Mil exp	0.0928	0.3896	0.0531	0.3717	0.0799	0.1457	0.1888	3	0.0405
Trade	0.0789	0.3526	0.4901	0.0676	0.1804	0.0153	0.1975	4	0.0541
Res	0.1762	0.2257	0.4013	0.2341	0.0317	0.0403	0.1849	3	0.0405
Notes: Water - Annual freshwater withdrawals, total (% of internal resources); CO2 - CO2 emissions (metric tons per capita); NO2 - Nitrous oxide emissions (thousand metric tons of CO2 equivalent); Cons - Electric power consumption (kWh per capita); Ren_Prod - Electricity production from renewable sources, excluding hydroelectric (% of total); Loss - Electric power transmission and distribution losses (% of output); Empl - Employment to population ratio, 15+, total (%) (modeled ILO estimate); Gini - Gini index; School - School enrollment, secondary (% gross); GDP_pc - GDP per capita (current US$); GCFCE - General government final consumption expenditure (% of GDP); GCF - Gross capital formation (% of GDP); Infl - Inflation, consumer prices (annual %); Mil_Exp - Military expenditure (% of GDP); Trade - Trade (% of GDP); Res - Total reserves in months of imports; Av. - average eigenvalue of individual indicator; Comp 1-6 - principal component. Source: Authors' calculations in Stata 14.2/SE software (Stata, 2024)

For the entire observation period, the most significant determinants of state national security are the Inflation, the NO2 emissions and the General government final consumption expenditure. Thus, the National Security Index for 34 European countries in 2000-2022 is calculated according to the formula:

NSI = 0.0946 * Water + 0.0541 * CO2 + 0.1081 * N02 + 0.0405 * Cons + 0.0811 (1)

¦ Ren_prod + 0.0135 * Loss + 0.0946 * Empl + 0.0676 * Gini + 0.0135

¦ School + 0.0270 * GDPpc + 0.1081 * GGFCE + 0.0405 * GCF + 0.1216

* Infl + 0.0405 * Md_exp + 0.0541 * Trude + 0.0405 * Res

Notes: NSI is National Security Index; Water - Annual freshwater withdrawals, total (% of internal resources); CO2 - CO2 emissions (metric tons per capita); NO2 - Nitrous oxide emissions (thousand metric tons of CO2 equivalent); Cons - Electric power consumption (kWh per capita);Ren_Prod - Electricity production from renewable sources, excluding hydroelectric (% of total); Loss - Electric power transmission and distribution losses (% of output); Empl - Employment to population ratio, 15+, total (%) (modeled ILO estimate); Gini - Gini index; School - School enrollment, secondary (% gross); GDP_pc - GDP per capita (current US$); GCFCE - General government final consumption expenditure (% of GDP); GCF - Gross capitalformation (% of GDP); Infl - Inflation, consumer prices (annual %); Mil_Exp - Military expenditure (% of GDP); Trade - Trade (% of GDP); Res - Total reserves in months of imports.

The dynamics of the National Security Index values for the studied 34 European countries in 2019-2022 and their chain growth rates are presented in Table 4.

Table 4. Dynamics of the National Security Index for 34 European countries in 2019-2022

Country	2019	2020	2021	2022	2020/2019	2021/2020	2022/2021
Albania	0.5595	0.5609	0.5670	0.5435	0.24	1.10	-4.15
Austria	0.6224	0.6302	0.6377	0.6304	1.26	1.18	-1.14
Belgium	0.6277	0.6442	0.6508	0.6526	2.64	1.02	0.27
Bosnia and Herzegovina	0.5608	0.5697	0.5598	0.5757	1.58	-1.74	2.85
Bulgaria	0.5515	0.5635	0.5594	0.5484	2.19	-0.73	-1.96
Croatia	0.6212	0.6438	0.6329	0.6263	3.64	-1.69	-1.05
Czechia	0.6287	0.6386	0.6459	0.6286	1.58	1.14	-2.68
Denmark	0.7183	0.7222	0.7260	0.7155	0.55	0.52	-1.44
Estonia	0.6312	0.6236	0.6184	0.6063	-1.20	-0.83	-1.95
Finland	0.6436	0.6528	0.6600	0.6596	1.43	1.10	-0.06
France	0.5281	0.5470	0.5481	0.5491	3.57	0.21	0.17
Germany	0.5498	0.5660	0.5722	0.5748	2.94	1.11	0.44
Greece	0.5637	0.5791	0.5803	0.5738	2.73	0.22	-1.13
Hungary	0.5689	0.5822	0.5887	0.5881	2.35	1.10	-0.09
Iceland	0.7092	0.7209	0.7084	0.7142	1.65	-1.73	0.82
Ireland	0.6531	0.6501	0.6284	0.6250	-0.47	-3.34	-0.53
Italy	0.5427	0.5651	0.5641	0.5632	4.13	-0.17	-0.15
Latvia	0.6245	0.6331	0.6365	0.6170	1.38	0.53	-3.06
Lithuania	0.6215	0.6247	0.6264	0.6192	0.51	0.26	-1.14
Moldova	0.5199	0.5357	0.5346	0.5820	3.04	-0.20	8.86
Netherlands	0.5949	0.6073	0.6176	0.6072	2.09	1.70	-1.68
North Macedonia	0.5582	0.5700	0.5729	0.5696	2.11	0.51	-0.59
Norway	0.6583	0.6738	0.6585	0.6276	2.35	-2.28	-4.69
Poland	0.5483	0.5560	0.5597	0.5548	1.39	0.68	-0.88
Portugal	0.6215	0.6316	0.6377	0.6311	1.63	0.96	-1.04
Romania	0.5630	0.5757	0.5646	0.5523	2.26	-1.93	-2.19
Serbia	0.5023	0.5106	0.5049	0.5044	1.63	-1.11	-0.09
Slovak Republic	0.6453	0.6461	0.6580	0.6510	0.13	1.84	-1.06
Slovenia	0.6216	0.6313	0.6371	0.6323	1.55	0.92	-0.75
Spain	0.5541	0.5694	0.5702	0.5658	2.76	0.13	-0.77
Sweden	0.6849	0.6880	0.6863	0.6827	0.45	-0.24	-0.53
Switzerland	0.6272	0.6457	0.6384	0.6257	2.95	-1.13	-1.99
Ukraine	0.5254	0.5302	0.5212	0.5097	0.91	-1.70	-2.19
UK	0.5606	0.5862	0.5877	0.5792	4.55	0.25	-1.44

Source: Authors' calculations

According to Table 4, the national security level did not decrease during the first year of the COVID-19 pandemic (with the exception of Estonia and Ireland). It indicates the time-delayed destructive impact of the pandemic on the state national security. In 2021 compared to 2020, the situation worsened for more countries. Within 2021 -2022, the National Security Index improvement was recorded only for Moldova, Iceland, France, Germany, Belgium, Bosnia and Herzegovina.

The next study stage is to determine significance of separate parameter impact on the overall level of state national security. Also, we observe transformation of these patterns during the pandemic period compared to the pre-pandemic period (Table 5).

Table 5 (cont.). Results of the weighting coefficients identification

Variable	General	2019	2020 Rank	2021	2022
	Rank	Weight	Rank	Weight	Rank	Weight	Rank	Weight	Rank	Weight
Water	7	0.0946	1	0.0122	4	0.0488	2	0.0244	6	0.0732
CO2	4	0.0541	8	0.0976	8	0.0976	5	0.0610	8	0.0976
NO2 |	8	0.1081	4	0.0488	4	0.0488	3	0.0366	5	0.0610
Cons	3	0.0405	3	0.0366	1	0.0122	6	0.0732	2	0.0244
Ren prod	6	0.0811	6	0.0732	8	0.0976	7	0.0854	5	0.0610
Loss	1	0.0135 |	9	0.1098	8	0.0976	8	0.0976	3	0.0366
Empl	7	0.0946	7	0.0854	5	0.0610	3	0.0366	9	0.1098
Ginny	5	0.0676	5	0.0610	6	0.0732	7	0.0854	5	0.0610
School	1	0.0135	3	0.0366	4	0.0488	4	0.0488	4	0.0488
GDP pc	2	0.0270	2	0.0244	3	0.0366	4	0.0488	3	0.0366
GGFC E |	8	0.1081	5	0.0610	8	0.0976	8	0.0976	3	0.0366
GCF	3	0.0405	2	0.0244	2	0.0244	1	0.0122	3	0.0366
Infl |	9	0.1216	8	0.0976	10	0.1220	9	0.1098	4	0.0488
Mil exp	3	0.0405	5	0.0610	7	0.0854	2	0.0244	1	0.0122
Trade	4	0.0541	7	0.0854	6	0.0732	8	0.0976	2	0.0244
Res	3	0.0405	7	0.0854	9	0.1098	7	0.0854	7	0.0854
Notes: Water - Annual freshwater withdrawals, total (% of internal resources); CO2 - CO2 emissions (metric tons per capita); NO2 - Nitrous oxide emissions (thousand metric tons of CO2 equivalent); Cons - Electric power consumption (kWh per capita); Ren_Prod - Electricity production from renewable sources, excluding hydroelectric (% of total); Loss - Electric power transmission and distribution losses (% of output); Empl - Employment to population ratio, 15+, total (%) (modeled ILO estimate); Gini - Gini index; School - School enrollment, secondary (% gross); GDP_pc - GDP per capita (current US$); GCFCE - General government final consumption expenditure (% of GDP); GCF - Gross capital formation (% of GDP); Infl - Inflation, consumer prices (annual %); Mil_Exp - Military expenditure (% of GDP); Trade - Trade (% of GDP); Res - Total reserves in months of imports; Av. - average eigenvalue of individual indicator; Comp 1-6 - principal component. Source: Authors' calculations

Thus, during the pandemic period, we see transformation of patterns to ensure significance of financial, socio-economic, and environmental determinants in the post-pandemic recovery of state national security.

Table 6 demonstrates the regression analysis results in identifying the relationship between the National Security Index and public health determinants.

Among the public health determinants, there are the following points:

• Capital health expenditure (% of GDP) (CHE);

• Current health expenditure (% of GDP) (CurHE);

• Hospital beds (per 1,000 people) (Beds).



Table 6. Results of the regression analysis on relationship between the National Security Index and public health determinants in 2019-2022 for 34 European countries

NSI	Coefficient	Standard error	t-value p-value	95% Confidence Interval	Sig
2019
CHE	-0.0447	0.0883	-0.51	0.6228	-0.2390	0.1497
CurHE	0.0040	0.0164	0.24	0.8121	-0.0320	0.0400
Beds	-0.0003	0.0122	-0.02	0.9818	-0.0271	0.0266
Constant	0.5754	0.1401	4.11	0.0017	0.2671	0.8837	***
2020
CHE	-0.0350	0.0854	-0.41	0.6902	-0.2230	0.1531
CurHE	-0.0075	0.0118	-0.64	0.5365	-0.0336	0.0185
Beds	0.0040	0.0114	0.35	0.7346	-0.0211	0.0290
Constant	0.6369	0.1126	5.66	0.0001	0.3891	0.8846	***
2021
CHE	-0.0403	0.0846	-0.48	0.6435	-0.2266	0.1460
CurHE	-0.0113	0.0085	-1.32	0.2135	-0.0301	0.0075
Beds	0.0058	0.0107	0.54	0.5978	-0.0178	0.0295
Constant	0.6567	0.0945	6.95	0.0000	0.4488	0.8647	***
2022
CHE	-0.0292	0.0734	-0.40	0.6988	-0.1907	0.1324
CurHE	0.0086	0.0143	0.60	0.5608	-0.0230	0.0402
Beds	0.0043	0.0111	0.39	0.7032	-0.0201	0.0288
Constant	0.5178	0.1116	4.64	0.0007	0.2723	0.7634	***

Notes: CHE - Capital health expenditure (% of GDP); CurHE - Current health expenditure (% of GDP) (CurHE); Beds - Hospital beds (per 1,000people) (Beds); Sig - significance; *** - significance at 99% confidence interval.

Source: Authors' calculations in Stata 14.2/SE software (Stata, 2024)

Table 6 shows neither in the pre-pandemic year nor in each of the pandemic years, there is no statistically significant influence of public health determinants on state national security.



Discussion

Bibliometric analysis conducted on 307 Scopus publications revealed that scientists get used to research post-pandemic recovery within three perspectives. The first cluster focuses on defining the impact of urban development, tourism, and employment on the post -pandemic recovery. The second cluster concerns ecological and innovative prerequisites for recovery after COVID-19. The third cluster assesses social, psychological and gender factors of the post-pandemic recovery. Bibliometric analysis proved that underlining of the post-pandemic recovery perspectives is in focus of scientists worldwide. Despite the leadership of British, American and Chinese scientists in publication activity on the topic, this problem is actively considered by academicians from all continents.

Thus, based on the theoretical generalisation, we can conclude that the post-pandemic recovery might be realised as a complex strategy. It considers curtain measures on micro-, subcentral, national and supranational levels. Moreover, these measures might be co-integrated and consistent with each other within general framework. Architectonics of the post-pandemic recovery strategy should consider social, economic, environmental, and public health aspects.

To fulfil the research objectives (to identify changes in empirical patterns for distinguishing the significance of financial, socio-economic, environmental and public health determinants of national security in pandemic and pre-pandemic periods), the National Security Index is constructed. The Index covers 16 proxies of the national security measurement, which characterise environmental, economic and social perspectives.

All indicators were brought to the comparable form with the natural and Savage normalisation. They also ranked the contribution significance in the integral index. Ranking was realised via the principal component analysis and the Fishburn approach. Within the country sample from 34 European countries, Denmark, Iceland, Sweden and Norway have the highest level of the National Security Index during 20002022.

Aiming identification of the COVID-19 influence of the National Security Index, we compare its chain growth rates during 2019-2022. This analysis showed that for most countries the Index value keeps growing in 2020 comparing with 2019. Italy (4.13%), Croatia (3.64%), and France (3.57%) demonstrate the most significant chain growth. Nevertheless, in Estonia and Ireland, the Index value decreased in the first year of the COVID-19 pandemic. This might bring to the conclusion about the vulnerability of socio-economic systems in these countries and their sensitivity to shocks of the pandemic.

The second pandemic year damaged almost half of the economies, which was revealed in the fall of the National Security Index. In 2021, Norway (-2.28%) and Romania (-1.93%) experienced the most dramatical decrease in the level of the performance indicator. Nevertheless, numerous countries still kept demonstrating the National Security Index growth in 2021. The Slovak Republic has the most considerable positive chain growth rate - 1.84%.

Negative impact of the COVID-19 pandemic proved to be significant in 2022. While most countries (28 out of 34) demonstrate decrease in the National Security Index, Belgium, Bosnia and Herzegovina, France, Germany, Iceland, and Moldova show growth in the performance indicator. It is also notable, that in Germany and France, there were no decrease in the National Security Index during the pandemic period. Thus, these socio-economic systems might be considered as benchmarks.

Within the research objectives, there is clarification of changes in the relative patterns of determinants contribution in state national security in pre-pandemic and pandemic periods. The same concerns weighing coefficients identified for each of the pandemic years via combination of the principal component analysis, Fishburn formula and ranking. Empirical results allow approving the hypothesis that COVID-19 pandemic provokes changes of relevance of social, economic and environmental determinants contribution to national security. These changes concern both the essence of determinants. In the pre-pandemic period, environmental and natural resources are crucial to ensure national security. In the pandemic period, economic and social parameters became dominant. The quantity of determinants is important as well (in pre-pandemic period, national security depends mostly on three indicators while during the pandemic up to six determinants obtained the maximal relativeness). The research findings demonstrate a shift in strategic priorities of national policies. They might be considered during the post-pandemic strategy development.

While clarifying the impact of public health determinants on national security, separate regression models were built for each of the pandemic years. Modelling results do not confirm the hypothesis about the relationship between national security and health care determinants.



Conclusions

Generalisation of theoretical findings on the post-pandemic recovery perspectives showed that there are three directions of research. Academicians consider that post-pandemic recovery crucially depends on urban, tourism and environmental recovery, investment attractiveness and innovation activity, mental health and social protection improvement.

Analysis during 2019-2022 estimated the dynamics and chain rates of the National Security Index for 34 European countries. Analysis showed that the biggest number of countries with the National Security Index decrease is in 2022. Moreover, in each subsequent year, the trend only worsened (in 2021 - 20 out of 34 countries demonstrated increase in the analysed parameter; in 2022 - only 6 out of 34 countries). In comparison, in 2020 there were no large-scale negative dynamics of changes in the National Security Index compared to 2019 (only two of the country sample reflected the negative chain growth rates). All of that confirmed the destructive pandemic impact on the performance index, which is slightly delayed in time. Based on identifying the significance of financial, socio-economic and environmental determinants contribution in national security during 2000-2022, national security might be ensured via limitation of inflation and NO2 emissions as well as expansion of the general government final consumption expenditure.

In turn, separately for the year before the pandemic, the most relevant parameters to ensure national security were the CO2 emission reduction, electric power transmission and distribution losses and lower inflation rates. Meanwhile, in the first pandemic year, the number of relevant factors doubled (due to a slight gap between the eigenvalues, the same ranks were assigned to the variables). Thus, in 2020, not only the inflation containment, CO2 emissions, and electric power transmission and distribution losses, but also the renewable energy promotion, the higher general government final consumption expenditure and total reserves in months of imports are traced. The findings claim the economic resilience became crucial in turbulent periods.

In 2021, 4 parameters were the most important (including the traditional inflation, the electric power transmission and distribution losses and the general government final consumption expenditure). However, the increase in foreign trade also gained importance. Thus, during the first pandemic year, the dominant role in state national security was ensured by environmental, energy and economic factors. In the following year, economic and trade determinants became far more important. In 2022, the state national security focused on balancing environmental, social and economic determinants. The most relevant was employment, CO2 emissions reduction and rise of total reserves in months of imports.

Summarising the obtained results on COVID-19, the state national security depended to a greater extent on various factors. However, for the post-pandemic recovery, it is necessary to curb inflation, strengthen energy independence, reduce greenhouse gas emissions, promote the public expenditure optimisation, employ people, maintain an insurance reserve for the system resilience due to the increase in total reserves in months of imports. It is this combination of targets that will help to recover the state national security level after the pandemic shocks. They may be absorbed and prevented from rapidly spreading in case of other similar threats in future.

In 2019-2022, there were also no statistically significant impacts of capital health expenditure (% of GDP), current health expenditure (% of GDP) and hospital beds on the National Security Index. Therefore, the change in certain public health factors did not affect the change in national security during the pandemic outbreak. That proves the absence of a clear close connection between these parameters but possible interrelationships between the parameters through channels of indirect influence. For example, effective public health system might contribute to improvement in labour force quality and productivity while increase of employment is one of the targets of the post-pandemic recovery strategy.



References

1. Abdal, A., & Ferreira, D. M. (2021). Deglobalisation, globalisation, and the pandemic: Current impasses of the capitalist world-economy. Journal of World-Systems Research, 27(1), 202-230. [CrossRef]

2. Arredondo-Trapero, F. G. et al. (2024). Competitiveness, quality education and universities: The shift to the post-pandemic world. Journal of Applied Research in Higher Education. [CrossRef]

3. Barbier, E. B. (2020). Greening the post-pandemic recovery in the G20. Environmental and Resource Economics, 76(4), 685-703. [CrossRef]

4. Berry, H. L. (2021). Enabling a youth- and mental health-sensitive greener post-pandemic recovery. World Psychiatry: Official Journal of the World Psychiatric Association (WPA), 20(2), 152-153. [CrossRef]

5. Carvalho, A., & Camacho, C. F. (2023). Addressing sustainability in Portuguese museums and heritage: The role of cultural policies. Heritage, 6(12), 7742-7754. [CroosRef]

6. Chen, Z. et al. (2020). Green stimulus in a post-pandemic recovery: The role of skills for a resilient recovery. Environmental and Resource Economics, 76, 901-911. [CrossRef]

7. Cheng, X. et al. (2024). Ride-sharing customers' self-protection motivation in the post-COVID-19 world. International Journal of Contemporary Hospitality Management, 36(4), 1114-1142. [CrossRef]

8. Deng, S. et al. (2024). Estimating fossil CO2 emissions from COVID -19 post-pandemic recovery in G20: A machine learning approach. Journal of Cleaner Production, 442, 140875. [CrossRef]

9. Descultu Grigore, M.-I. et al. (2024). Geotourism, a new perspective of post-COVID-19 pandemic relaunch through travel agencies. Case study: Bucegi Natural Park, Romania. Sustainability, 16(3), 985. [CrossRef]

10. Dingle, G. A. et al. (2024). Data from four consecutive cohorts of students in Australia (2019-2022) show the impact of the COVID-19 pandemic on domestic and international university students ' mental health. Australian & New Zealand Journal of Psychiatry. [CrossRef]

11. Fu, X. (2020). Digital transformation of global value chains and sustainable post-pandemic recovery. Transnational Corporations Journal, 27(2), 157-166. [Link]

12. Fu, X. et al. (2020). Introduction to the special section: The impact of COVID-19 and post-pandemic recovery: China and the world economy. Journal of Chinese Economic and Business Studies, 18(4), 311-319. [CrossRef]

13. Gerwe, O. (2021). The COVID-19 pandemic and the accommodation sharing sector: Effects and prospects for recovery. Technological Forecasting and Social Change, 167, 120733. [CrossRef]

14. Gozzoli, R. B. et al. (2024). Resilience model for a destination support: Pattaya, Thailand.

Heliyon, 10(4), e26599. [CrossRef]

15. Gustafsson, J. et al. (2023). Mental health profiles of Finnish adolescents before and after the peak of the COVID-19 pandemic. Child and Adolescent Psychiatry and Mental Health, 17, 54. [CrossRef]

16. Hammad, H. M. et al. (2023). Impacts of COVID-19 pandemic on environment. Society and food security. Environmental Science and Pollution Research, 30, 99261-99272. [CrossRef]

17. Ioakimidis, V., & Maglajlic, R. A. (2021). Post-pandemic recovery requires `more and better' mental health services. The British Journal of Social Work, 51(3), 791-793. [CrossRef]

18. Ivanov, D. (2021). Exiting the COVID-19 pandemic: After-shock risks and avoidance of disruption tails in supply chains. Annals of Operations Research. [CrossRef]

19. Ivanov, D., & Dolgui, A. (2021). A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning and Control, 32(9), 775-788. [CrossRef]

20. Jackson, L. et al. (2024). A consensus statement on perinatal mental health during the COVID-19 pandemic and recommendations for post-pandemic recovery and re-build. Frontiers in Global Women's Health, 5,1347388. [CrossRef]

21. Jain, A. et al. (2020). SARS-CoV-2 impact on elective orthopaedic surgery: Implications for postpandemic recovery. Journal of Bone and Joint Surgery, 102(13), E68. [CrossRef]

22. Jia, H. et al. (2024). Big data-driven spatio-temporal heterogeneity analysis of Beijing's catering service industry during the COVID-19 pandemic. Scientific Reports, 14, 721. [CrossRef]

23. Kikstra, J. S. et al. (2021). Climate mitigation scenarios with persistent COVID -19-related energy demand changes. Nature Energy, 6, 1114-1123. [CrossRef]

24. Klarin, A. et al. (2024). The slow movements: Informetric mapping of the scholarship and implications for tourism and hospitality. Journal of Hospitality & Tourism Research, 48(3), 464-482. [CrossRef]

25. Le Billon, P. et al. (2021). Fossil fuels, climate change, and the COVID-19 crisis: Pathways for a just and green post-pandemic recovery. Climate Policy, 21(10), 1347-1356. [CrossRef]

26. Natalia, D., & Syakurah, R. A. (2021). Mental health state in medical students during COVID-19 pandemic. Journal of Education and Health Promotion, 10, 208. [CrossRef]

27. Nguyen, H. T. T., & Nguyen, T. X. (2023). Understanding customer experience with Vietnamese hotels by analysing online reviews. Humanities & Social Sciences Commununications, 10, 618. [CrossRef]

28. Novikova, O. et al. (2021). The potential of digitalisation and social dialogue in ensuring postpandemic labour market sustainability: Priorities for Ukraine. Studies of Transition States and Societies, 13(2), 70-85. [CrossRef]

29. O'Sullivan, D. et al. (2020). The impact and implications of COVID-19: An Australian perspective. International Journal of Community and Social Development, 2(2), 134-151. [CrossRef]

30. Qian, Y., & Fan, W. (2020). Who loses income during the COVID-19 outbreak? Evidence from China. Research in Social Stratification and Mobility, 68, 100522. [CrossRef]

31. Qiu, R. T. R. et al. (2020). Social costs of tourism during the COVID-19 pandemic. Annals of Tourism Research, 84, 102994. [CrossRef]

32. Santiago, F. et al. (2024). Global trends and world order: Implications for new industrial policies in developing countries. Journal of Industry, Competition and Trade, 24(1), 5. [CrossRef]

33. Scopus (2024). [Link].

34. Shulla, K. et al. (2021). Effects of COVID-19 on the Sustainable Development Goals (SDGs). Discover Sustainability, 2(1), 15. [CrossRef]

35. Stata software (2024). [Link]

36. Vasylieva, T. et al. (2022). Economic development and income inequality: Role in country resistance to COVID-19. Economics and Sociology, 15(4), 286-302. [CrossRef]

37. VOSviewer software (2024). [Link]

38. Vysochyna, A. et al. (2023). Public health and national security proxies: Case of European countries. Journal of International Studies, 16(3), 219-237. [CrossRef]

39. Wei, X. et al. (2024). Understanding store-loyal customers' mobile channel migration: A trust-transfer perspective. International Journal of Retail & Distribution Management. [CrossRef]

40. World Bank DataBank (2024). [Link]