<abstract xmlns="http://www.w3.org/1999/xhtml">

<bold>Research purpose.</bold> The study is focused on the Covid-19 pandemic crisis in the European Union. This study investigates the current driving trends and trade-offs of the Covid-19 pandemic phenomenon and social inclusion trends in the European countries.
<bold>Design / Methodology / Approach.</bold> The methodology is based on conventional statistical index theory and statistics. The study investigates cases, deaths, and key Covid-19 statistics. The research design combines key social inclusion statistics of the Eurostat and the official Covid-19 statistics of the European Centre for Disease Prevention and Control. Covid-19 data is updated to 1.3.2021. Social inclusion variables are selected from the Eurostat database. Social inclusion variables cover poverty, material deprivation, income distribution, income, quality of life, employment, and education matters. Scattering matrices on the relationships among the key variables under review are reported.
<bold>Findings.</bold> The study reports basic trends of Covid-19 cases, deaths, deaths/cases and calculates these Covid-19 trends in 29 European countries. This study reports trade-off analyses of key social inclusion trends of the European Union countries. Key indicators are linked to economic income, income distribution, poverty, gender issues, and housing statistics. The 19 key indicators of social inclusion are analysed and reported with Covid-19 data. Statistical correlation analysis tables (2a and 2b) are calculated with key European social inclusion indicators. The study reveals some relevant aspects of the social inclusion policy of the European Union about the ongoing Covid-19 crisis and exit strategies.
<bold>Originality / Value / Practical implications.</bold> This conference paper demonstrates novel and exciting possibilities of integrated data pooling (The Eurostat and the European Centre for Disease Prevention and Control). Original results of key trend drivers are provided by the authors. Value-adding and interesting results are delivered for European governments and the business community. Results and findings of the study can be used in the planning of economic recovery and Covid-19 exit policies in the member states of the European Union.
</abstract>

Research purpose. The study is focused on the Covid-19 pandemic crisis in the European Union. This study investigates the current driving trends and trade-offs of the Covid-19 pandemic phenomenon and social inclusion trends in the European countries.
Design / Methodology / Approach. The methodology is based on conventional statistical index theory and statistics. The study investigates cases, deaths, and key Covid-19 statistics. The research design combines key social inclusion statistics of the Eurostat and the official Covid-19 statistics of the European Centre for Disease Prevention and Control. Covid-19 data is updated to 1.3.2021. Social inclusion variables are selected from the Eurostat database. Social inclusion variables cover poverty, material deprivation, income distribution, income, quality of life, employment, and education matters. Scattering matrices on the relationships among the key variables under review are reported.
Findings. The study reports basic trends of Covid-19 cases, deaths, deaths/cases and calculates these Covid-19 trends in 29 European countries. This study reports trade-off analyses of key social inclusion trends of the European Union countries. Key indicators are linked to economic income, income distribution, poverty, gender issues, and housing statistics. The 19 key indicators of social inclusion are analysed and reported with Covid-19 data. Statistical correlation analysis tables (2a and 2b) are calculated with key European social inclusion indicators. The study reveals some relevant aspects of the social inclusion policy of the European Union about the ongoing Covid-19 crisis and exit strategies.
Originality / Value / Practical implications. This conference paper demonstrates novel and exciting possibilities of integrated data pooling (The Eurostat and the European Centre for Disease Prevention and Control). Original results of key trend drivers are provided by the authors. Value-adding and interesting results are delivered for European governments and the business community. Results and findings of the study can be used in the planning of economic recovery and Covid-19 exit policies in the member states of the European Union.

European COVID -19 Pandemic Data and Social Inclusion Policy in the European Union: Drivers-Driven Trend Analysis

Economics and Culture

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Research purpose. The study is focused on the Covid-19 pandemic crisis in the European Union. This study investigates the current driving trends and trade-offs...

European COVID -19 Pandemic Data and Social Inclusion Policy in the European Union: Drivers-Driven Trend Analysis

Publicado en línea: 17 jun 2021

Páginas: 82 - 99

DOI: https://doi.org/10.2478/jec-2021-0007

Palabras clave
Covid-19, Pandemic data analytics, Social inclusion, European Union, Trend analysis, Trend drivers, Trade-offs analysis

© 2021 Jari Kaivo-oja et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

European COVID -19 Pandemic Data and Social Inclusion Policy in the European Union: Drivers-Driven Trend Analysis

Publicado en línea: 17 jun 2021

Páginas: 82 - 99

DOI: https://doi.org/10.2478/jec-2021-0007

Palabras claveCovid-19, Pandemic data analytics, Social inclusion, European Union, Trend analysis, Trend drivers, Trade-offs analysis

© 2021 Jari Kaivo-oja et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Palabras clave
Covid-19, Pandemic data analytics, Social inclusion, European Union, Trend analysis, Trend drivers, Trade-offs analysis