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The Application of Association Rules to Detect the Effects of Vaccinations against Covid-19 in the EU-27. Preliminary Estimates

100%
Berezka K.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2023
|
vol. 27
|
issue 1
1-16
PL
W tym badaniu autorzy uzyskali wstępną ocenę skuteczności wykrywania szczepień przeciwko COVID-19 w UE-27. Empiryczną podstawą badania jest dzienna liczba zachorowań na COVID-19, szczepień, hospitalizacji i zgonów w krajach UE w okresie od marca 2020 do marca 2022 r. Reguły asocjacji posłużyły do zidentyfikowania nieoczywistych powiązań między szczepieniami przeciwko COVID-19 oraz przypadków zachorowań, hospitalizacji i zgonów z powodu COVID-19. Uzyskane wyniki posłużyły do grupowania krajów UE według poziomu szczepień przeciwko COVID-19, przypadków choroby, zgonów z jej powodu oraz hospitalizacji dla krajów członkowskich UE. Do analizy skupień zastosowano metodę k-średnich grupowania. Ujawniono ukryte zależności liczby zachorowań na COVID-19, liczby hospitalizacji z powodu COVID-19 oraz liczby zgonów z powodu COVID-19 w związku z liczbą szczepień przeciwko COVID-19 w krajach UE. Stwierdzono z dużym prawdopodobieństwem, że szczepienia istotnie wpływają na poziom zachorowalności. Po raz pierwszy uzyskano reguły asocjacyjne, które są wstępnymi szacunkami zależności między dynamiką szczepień przeciwko COVID-19 a dynamiką zachorowań na COVID-19, hospitalizacji z tego powodu i zgonów w krajach UE. Wyniki mogą posłużyć do podejmowania korzystnych decyzji, np. do uregulowania polityki szczepień w poszczególnych krajach UE i przewidywania przyszłych konsekwencji choroby.
EN
In this research study, the authors obtained the preliminary evaluation of the impact detection of vaccinations against COVID-19 in the EU-27. The empirical basis of the study was the daily number of COVID-19 cases, vaccinations, hospitalisations, and deaths in the EU countries from March 2020 to March 2022. Rules of association were used to identify non-obvious associations between vaccinations against COVID-19 and cases of illness, hospitalisations, and deaths from COVID-19. The obtained results were used to cluster the EU countries by the level of vaccinations against COVID-19, cases of COVID-19, deaths from COVID, and COVID-19 hospitalisations for the EU member states. The K-means clustering method was used for cluster analysis. Hidden dependencies of the number of COVID-19 cases, the number of COVID-19 hospitalisations, and the number of COVID-19 deaths due to the number of vaccinations against COVID-19 by EU countries were revealed. It was established with a high probability that vaccination significantly affects the level of morbidity. For the first time, association rules were obtained, which are preliminary estimates of the relationship between the dynamics of vaccinations against COVID-19 and the dynamics of COVID-19 cases, COVID-19 hospitalisations, and deaths from COVID-19 in the EU. The results can be used to make beneficial decisions, for example, to regulate vaccination policies in individual EU countries, and predict the future consequences of the COVID-19 pandemic.
2
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Сorrespondence analysis as a tool for computer modeling of sustainable development

63%
Berezka K., Kovalchuk O.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2018
|
issue vol. 22 no. 4
9-23
EN
Many of the problems that the world faces today appeared as the result of unstable development. Global climate change, resource depletion, space debris, poverty, inequality, and threats to global security are the main but not the only challenges for modern humanity. The important issue in studying the problems of sustainable development of the countries in the world is the development of strategies that would give an opportunity to avoid environmental and social catastrophes. The correspondence analysis is used to identify the relationship between the Happy Planet Index (which is an aggregate indicator of achievements in the key aspects of human development, such as life duration and quality, distribution uniformity, access to knowledge, and preservation of environment) and Gross National Income (one of the basic metrics of the population welfare level). The analysis led to the conclusion that the income level of the population is not the main factor in assessing the level of sustainable development of a country. The obtained results can give important and useful information for social institutions and politicians.
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