Object

Title: The Application of Association Rules to Detect the Effects of Vaccinations against COVID-19 in the EU-27. Preliminary estimates

Title in english:

Stosowanie zasad stowarzyszenia w celu wykrywania skutków szczepionek przeciwko COVID-19 w UE-27. Wstępne szacunki

Creator:

Berezka, Kateryna ; Kovalchuk, Olha

Description:

Econometrics = Ekonometria, 2023, Vol. 27, No. 1, s. 1-16

Abstrakt:

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.

Publisher:

Publishing House of Wroclaw University of Economics and Business

Place of publication:

Wrocław

Date:

2023

Resource Type:

artykuł

Resource Identifier:

doi:10.15611/eada.2023.1.01 ; oai:dbc.wroc.pl:121743

Language:

eng

Relation:

Econometrics = Ekonometria, 2023, Vol. 27, No. 1

Rights:

Pewne prawa zastrzeżone na rzecz Autorów i Wydawcy

Access Rights:

Dla wszystkich zgodnie z licencją

License:

CC BY-SA 4.0

Location:

Uniwersytet Ekonomiczny we Wrocławiu

Group publication title:

Ekonometria = Econometrics

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