Multiple Correspondence Analysis and Hierarchical Clustering of Occupational Exposure to COVID-19 Among Healthcare Workers in Castilla y León, Spain

The COVID-19 pandemic represents a major challenge for healthcare systems, particularly affecting healthcare workers (HCW) due to their higher occupational risk. A retrospective observational study was conducted using data from 239,188 diagnostic tests performed on HCW from the Castilla y León (Spain) Health Service between March 2020 and March 2022. The objective was to explore associations between categorical variables, such as geographic areas, job categories, and infection status, through Multiple Correspondence Analysis and Hierarchical Clustering. The results revealed higher infection rates among HCW in regions near Madrid and in job categories with a greater care-related workload. These findings help identify risk factors and support the development of more effective occupational hazard prevention and health interventions to reduce infection risk and improve preventive measures.

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Journal
Mathematics
Published
2025-11-07
DOI
https://doi.org/10.3390/math13223574
Primary Topic
Infection Control and Ventilation
Type
article
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article

Multiple Correspondence Analysis and Hierarchical Clustering of Occupational Exposure to COVID-19 Among Healthcare Workers in Castilla y León, Spain

Araceli Queiruga‐Dios, Purificación Vicente‐Galindo, Verónica Carrasco-Bonal
Mathematics
Infection Control and Ventilation
article

Multiple Correspondence Analysis and Hierarchical Clustering of Occupational Exposure to COVID-19 Among Healthcare Workers in Castilla y León, Spain

Araceli Queiruga‐Dios, Purificación Vicente‐Galindo, Verónica Carrasco-Bonal
article en

Abstract

The COVID-19 pandemic represents a major challenge for healthcare systems, particularly affecting healthcare workers (HCW) due to their higher occupational risk. A retrospective observational study was conducted using data from 239,188 diagnostic tests performed on HCW from the Castilla y León (Spain) Health Service between March 2020 and March 2022. The objective was to explore associations between categorical variables, such as geographic areas, job categories, and infection status, through Multiple Correspondence Analysis and Hierarchical Clustering. The results revealed higher infection rates among HCW in regions near Madrid and in job categories with a greater care-related workload. These findings help identify risk factors and support the development of more effective occupational hazard prevention and health interventions to reduce infection risk and improve preventive measures.

MathematicsVol. 13(22)
Universidad de Salamanca (ES)
Openalex Percentile: Top 52%
Infection Control and Ventilation
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Multiple Correspondence Analysis and Hierarchical Clustering of Occupational Exposure to COVID-19 Among Healthcare Workers in Castilla y León, Spain — Araceli Queiruga‐Dios, Purificación Vicente‐Galindo, et al. · Mathematics (2025) | TGRS Research Map | TGRS