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The purpose of this paper is to assess the level of material deprivation in European Union countries in 2016 from both a local and a global perspective. The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was used in the study. Based on research, five main types of the level of the material deprivation of European Union countries were identified. Research findings suggest that the population of old EU countries is less severely affected by material deprivation than people living in new member states. Also, the level of global material deprivation was assessed. The study was based on 2016 statistical data delivered by Eurostat. [ABSTRACT FROM AUTHOR]

The main research question concerned the identification of changes in the COVID-19 epidemiological situation using fuzzy clustering methods. This research used cross-sectional time series data obtained from the European Centre for Disease Prevention and Control. The identification of country types in terms of epidemiological risk was carried out using the fuzzy c-means clustering method. We also used the entropy index to measure the degree of fuzziness in the classification and evaluate the uncertainty of epidemiological states. The proposed approach allowed us to identify countries' epidemic states. Moreover, it also made it possible to determine the time of transition from one state to another, as well as to observe fluctuations during changes of state. Three COVID-19 epidemic states were identified in Europe, i.e., stabilisation, destabilisation, and expansion. The methodology is universal and can also be useful for other countries, as well as the research results being important for governments, politicians and other policy-makers working to mitigate the effects of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]