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

Year: 2025

Type: article

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.

Source: Mathematics

DOI: 10.3390/math13223574

Authors: Verónica Carrasco-Bonal, Purificación Vicente-Galindo, Araceli Queiruga-Dios

Institution: Universidad de Salamanca

Language: English

Topic: COVID-19 epidemiological studies

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

SDGs: Good health and well-being, Decent work and economic growth

Open Access status: gold

Estimated APC paid: $3,137