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

Verónica Carrasco-Bonal (), Purificación Vicente-Galindo and Araceli Queiruga-Dios ()
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Verónica Carrasco-Bonal: Department of Statistics, Faculty of Medicine, Universidad de Salamanca, Calle Alfonso X El Sabio, s/n, 37007 Salamanca, Spain
Purificación Vicente-Galindo: Department of Statistics, Faculty of Medicine, Universidad de Salamanca, Calle Alfonso X El Sabio, s/n, 37007 Salamanca, Spain
Araceli Queiruga-Dios: Department of Applied Mathematics, Higher Technical School of Industrial Engineering, Universidad de Salamanca, 37700 Bejar, Spain

Mathematics, 2025, vol. 13, issue 22, 1-21

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.

Keywords: COVID-19; occupational health; occupational hazard prevention; diagnostic testing; multivariate analysis; hierarchical clustering (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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