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Social and economic variables explain COVID-19 diffusion in European regions
Christian Cancedda1, Alessio Cappellato1, Luigi Maninchedda2
1Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Turin, Italy.
Scientific Reports
|March 14, 2024
Summary
High COVID-19 prevalence in European regions was linked to more time spent at work and higher life expectancy. Factors like education and employment status also played a role in case distribution.
Area of Science:
- Epidemiology
- Public Health
- Socioeconomics
Background:
- Italy, particularly Lombardy, experienced the highest COVID-19 cases globally in early 2020.
- Understanding regional variations in COVID-19 prevalence is crucial for public health interventions.
Purpose of the Study:
- To identify key variables influencing COVID-19 case prevalence in Lombardy and other highly-affected European regions.
- To analyze factors across the first and second pandemic waves.
Main Methods:
- Utilized a dataset of 22 variables spanning economy, population, healthcare, and education.
- Employed binary classifiers to identify high-prevalence regions.
- Determined the most relevant variables for classification and assessed analysis robustness.
Main Results:
- High number of hours spent in work environments was a significant predictor.
- Higher life expectancy was associated with increased prevalence.
- Low rates of individuals disengaging from education and employment (NEET) were also identified as relevant.
Conclusions:
- Socioeconomic and demographic factors significantly correlate with COVID-19 prevalence.
- Work environment, life expectancy, and education/employment status are key indicators for identifying high-risk regions.
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