Predictive Risk Modeling and Quantitative Analysis of Microbial Contamination in Hospital Textiles

Abstract

This quantitative observational study examined microbial contamination in hospital textiles using predictive risk modeling and multivariable statistical analysis to identify determinants of contamination across textile categories, operational pathways, and clinical contexts. A cross-sectional analytic design was applied in a multi-unit hospital setting, and a total of 360 reusable textile items were sampled, including bed linens (40.0%), staff uniforms (25.0%), towels (20.0%), and privacy curtains (15.0). Items were collected from both high-acuity units (35.0%) and general wards (65.0%) and were linked to structured metadata describing exposure duration, contact density proxies, handling and transport conditions, laundering characteristics, storage duration, and textile reuse indicators. Microbial contamination outcomes were measured as microbial burden and contamination positivity, with positivity observed in 46.5% of linens, 48.6% of towels, 34.4% of uniforms, and 29.6% of curtains. Descriptive analysis demonstrated highly skewed contamination distributions, with median microbial burden values ranging from 2.0 to 3.4 units across textile categories and higher exposure duration observed for curtains and uniforms compared with linens and towels. Multivariable regression analysis showed that textile category, exposure duration, contact density, ward acuity, handling pathway quality, laundering quality, and post-laundering storage time were independently associated with contamination outcomes after adjustment for clustering by ward and laundering batch. In the microbial burden model, towels (adjusted estimate = 1.35, p < 0.001) and linens (1.28, p = 0.001) exhibited higher burden relative to uniforms, while curtains showed lower burden (0.82, p = 0.041). In the contamination positivity model, towels (adjusted odds ratio = 1.84, p = 0.009) and linens (1.62, p = 0.019) demonstrated higher odds of positivity. High-acuity wards were associated with increased contamination outcomes in both models. Laundering quality demonstrated a protective association with microbial burden (0.88, p < 0.001) and positivity (0.86, p = 0.003), while longer post-laundering storage increased contamination risk. Overall, the findings demonstrated that hospital textile contamination followed systematic and quantifiable patterns shaped by textile type, exposure dynamics, operational handling, laundering performance, and clinical context, supporting the use of multivariable and hierarchical modeling approaches for contamination risk assessment in healthcare textile systems.