The article summarizes the arguments and counterarguments in the scholarly discussion about the problem of choosing a model of healthcare organization. The study’s primary goal was to identify the economic efficiency of the public health system and resistance to COVID-19. The relevance of addressing this research issue is that the epidemiological challenges posed by the pandemic worldwide have manifested themselves differently in various countries. Therefore, it is advisable to consider the effectiveness of public healthcare models and how they have worked out in the fight against COVID-19. Research in the work was carried out in the following logical sequence: conducting scientometric analysis of research, creation of a statistical research base for 22 countries of the world; construction of integral indices of the economic efficiency of the health care system; calculation of public health system resilience to the COVID-19 pandemic; application of frontier DEA analysis to determine system efficiency; comparison and analysis of the results of research on the economic efficiency of public health systems obtained by different methods. The article presents the results of a comparison of the economic efficiency of the public health system, which showed that the system built according to the Beveridge principle is the most resistant to the pandemic and, at the same time, has the highest indices of economic efficiency.

The purpose of the study is to analyze the presence of functional interrelationships between the level of funding of the healthcare sector and the country’s ability to withstand any pandemic, using the example of the COVID-19 pandemic. Official indicators presented by the WHO, analytical reports by Numbeo (the world’s largest cost-of-living database), and the Global Health Security Index were used for the study. Using these indicators, the authors analyzed the following: the level of the spread of coronavirus infections in the world’s countries, the share of public expenditures on the development of the medical sphere in the GDP of the countries, and the development of the healthcare sector in 12 developed countries and Ukraine. These countries were grouped into three groups, based on the model of the organization of the healthcare sector (Beveridge model, Bismark model, Market (private) model). The Farrar–Glauber method was used to check for multicollinearity in the input dataset, and thirteen relevant indicators were selected. These indicators took part in the formation of the generalized characteristics of the country’s medical sphere and the ability to resist the pandemic. The state of readiness of countries to resist the spread of coronavirus infections was assessed using the country’s index of vulnerability to COVID-19 and the integral index of the development of medicine. Additive convolution was used in combination with sigma-limited parameterization to form an integral index of the country’s vulnerability to COVID-19 and to determine the weights of each indicator. The convolution of indicators according to the Kolmogorov–Gabor polynomial was used to construct an integral index of the development of medicine. Thus, while analyzing the ability of countries to resist the pandemic in terms of models of organization of the healthcare sector, it should be noted that none of the models demonstrated absolute effectiveness in the fight against the mass spread of COVID-19. The calculations made it possible to determine the nature of the relationship between the integral indices of the development of medicine and the vulnerability of countries to COVID-19, as well as a country’s potential ability to resist any pandemic and prevent the mass spread of infectious diseases.

The article focuses on measuring the fluctuations in countries’ development as a result of the COVID-19 pandemic. The obtained measures make it possible to predict the extent of the impact of risks to public health on the economy, financial-budgetary, political-institutional development of states in the future, as well as the social determinants of public health. This assessment represents a new paradigm that makes it possible to effectively evaluate the manifestations of the consequences of COVID-19 and to identify the relevant determinants of the lack of resilience of the medical and social security systems to the coronavirus pandemic around the world. We picked the determinant of national development indicators of the 59 countries in order to measure the fluctuations in their economic development. In addition, we applied the binary response model for identifying the economic, financial-budgetary, and political-institutional development change with the happiness index of the countries being the dependent variable. The analysis of our empirical model made it possible for us to conclude that economic and financial-budgetary components have significantly increased the influence on well-being during the COVID-19 pandemic. In contrast, we observed the decrease in the impact of political and institutional indicators during the same period.

The article examines the cases of 18 countries that have been consistently ranked by Esports Earnings over the past ten years to find the social and economic determinants that may determine a country’s success in the international e-sports arena. In the study, indicators of a country’s cybersports success consider the annual volume of prizes won by its e-sportsmen, the ranking place in the world rankings and the total number of e-sportsmen. The hypothesis about the possible influence of a number of macroeconomic indicators, as well as the characteristics of the overall level of social stability on the development of e-sports within the country, was put forward and verified. The scientific landscape of research on cybersports, published in Scopus (by prevailing research topics, the geography of research network leaders, and the evolution of scientific search), was structured using the VOSviewer toolkit. By means of canonical analysis, pairwise relationships in the chain “economic development – social development – e-sports development,” as well as determinants with strong intragroup and intergroup relationships, have been revealed; and these relationships were quantified in the aggregate by means of structural modeling. The results of the calculations showed that the economic stability of the country rather than social stability has a greater influence on its success in the international e-sports arena. The most relevant indicators of economic development, considering success in e-sports, are GDP, unemployment rate and direct foreign investments, social development – poverty rate, population migration and Gini coefficient.

This article summarizes the arguments and counterarguments in the framework of the scientific discussion on the problem of identifying, using the Granger test, the components of macroeconomic stability of Ukraine most sensitive to the destructive impact of Covid-19. The study’s primary goal is to select from among many macroeconomic indicators precisely those that cause epidemiological surges in morbidity and mortality of the population using the example of the Covid-19 pandemic. The systematization of literary sources and approaches to solving the problem of finding determinants that affect the course of the pandemic shows many views among the scientists of the world. Still, they do not establish a single opinion. The study of the topic of identifying the influence of indicators of macroeconomic stability on the destructive impact of the pandemic in work is carried out in the following logical sequence: 1) systematization of literary sources according to the topic of the study; 2) creation of a statistical database that meets the requirements of the chosen methods; 3) bringing the obtained time series to a comparative form and achieving their stationarity; 4) conducting a two-sided test to identify causality. The methodological tools of the research methods were the Dickey-Fuller test for detecting a unit root and stationarity of a series, ways to achieve stationarity of a series using different methods, and a two-sided Granger test for detecting the causality of indicators. The object of the study is Ukraine; the term of the study is the beginning of the pandemic from February 2020 to December 2021. The article presents the results of an empirical analysis of the identification of the components of macroeconomic stability of Ukraine most sensitive to the destructive impact of Covid-19, which showed that such indicators exist and the causal relationship exists in both directions. The study empirically confirms and theoretically proves that the most influential factors are the consumer price index and inflation, which cause the variability of the number of infected and deaths in Ukraine. The study results can help create regional and national patterns of resistance to the destructive impact of the pandemic on macroeconomic stability.

This paper summarizes the arguments and counter-arguments in the scholarly debates on transformations in healthcare budgeting that should consider the differentiated regional vulnerability in responding to the pandemic. The primary purpose of the study is to identify priorities for local health development programs. The urgency of solving this problem is that the pandemic has revealed the unprecedented unpreparedness of the health care system to respond effectively to challenges; also, hidden problems accumulated during the last decades, which increase the emerging risks. The study is carried out in the following logical sequence: 1) collection, processing, and analysis of statistical data; 2) conducting a cluster analysis for group regions by vulnerability to different classes of diseases; 3) conducting correlation and regression analysis to compare the effects of the COVID-19 pandemic (cases and deaths) and the state of the region; 4) selection of the most significant features of the vulnerability of the region; 5) designing the matrix of the choice of priorities for financing targeted programs in the field of health care. Methodological tools of the study were methods of correlation and regression analysis, cluster analysis, testing for autocorrelation by Darbin — Watson method, sigma limited parameterization to identify the most significant coefficients. The method is tested for 25 regions of Ukraine (including Kyiv), as they can serve as pilots for other regions with similar demographic and economic characteristics. The article presents the results of an empirical analysis of the readiness of regions for critical conditions, such as COVID-19. Identifying such readiness and appropriate distribution of regions by disease classes allows to make decisions in financing and budgeting and improve the quality of health care. Keywords: COVID-19, regional vulnerability to COVID-19, step-by-step nonlinear regression, morbidity, mortality, regional profile, pandemic, multicollinearity, targeting budgeting. JEL Classification C21, C51, C31, C12, I15, I18, R58, R11 Formulas: 9; fig.: 5; tabl.: 7; bibl.: 36.