A fuzzy clustering approach to evaluate individual competencies from REFLEX data

COVID-19 vaccination reluctance across Europe: Lessons for the future

BACKGROUND

Vaccine reluctance is both a complex and context-specific issue and is the result of many complicating factors that need to be addressed more systematically. In Europe, several country-based ad-hoc studies have been carried out on COVID-19 vaccines/vaccination and vaccine reluctance but a comprehensive overview covering all 27 European Union (EU27) countries is lacking. Such study can help understand vaccine reluctance in the overall EU as well as examine differences between individual countries.

METHODS

This study relies on data from Flash Eurobarometer 505, covering all 27 European Union member states; the sample size is N=26,641. It takes a fuzzy clustering approach to construct typologies of attitudes towards COVID-19 vaccination, and subsequently develops an "Index of Attitudes" (IA) which accounts for individual positioning of EU citizens. The data analysis is based on grade of membership (GoM) model which is a reliable statistical tool to tackle heterogeneous populations.

RESULTS

The output of GoM model unveiled a hierarchical fuzzy 3-partition corresponding to three clearly identified typologies of feelings towards COVID-19 vaccination: Typology 1 entails favourable feelings while moderate-favourable feelings describe the Typology 2. Finally, Tipology 3 encompasses the scepticism towards COVID-19 vaccines. The IA, which quantifies the sentiment of European citizens towards COVID-19 vaccination in a 0-1 scale, reveals that although EU27 citizens overall are not against COVID-19 vaccination (index mean =0.44) some, mostly in eastern countries, deviate from this prevailing trend.

CONCLUSION

Distrust in the safety and efficacy of all kinds of vaccines, as well as a generalised distrust in European and national institutions, are associated with the reluctance in relation towards COVID-19 vaccination. However, this reluctance varies across countries. The outcomes of our study not only inform national government and health care agents but also help define communication strategies to reach the most reluctant citizens. The segmentation it provides makes it easier to customise campaigns that raise awareness of the consequences of not being vaccinated, particularly as new SARS-CoV-2 variants emerge.

Index of Satisfaction with Public Transport: A Fuzzy Clustering Approach

Increasing public transport use is recognized by many countries as crucial to the pursuit of a global strategy for environmental sustainability and improving urban mobility. Understanding what users value in a public transport service is essential to carry out this strategy. Using fuzzy clustering, we developed an index that measures individual user satisfaction with the public transport service in the metropolitan area of Lisbon and subsequently identified the possible determinants of satisfaction by means of a regression tree model. The results achieved unveil a hierarchical partition of the data, highlighting the diversified level of satisfaction among public transport users that is reflected in the distribution of the index. The managerial implications of the findings for the public transport service are addressed.