Mostafa Eissa
A non-parametric framework for analyzing spatial heterogeneity and contamination pathways in healthcare environments
Journal title : Universal Journal of Pharmaceutical Research
Publisher : Society of Pharmaceutical Tecnocrats
Print ISSN : 2831-5235
424 Views Original Article
Background:The systematic management of microbial bioburden in Class C healthcare cleanrooms is a critical factor in patient safety. Standard environmental monitoring often overlooks the complex spatial and statistical relationships of contamination. This study applies a rigorous statistical framework to a comprehensive environmental monitoring dataset to accurately map contamination risk.Methods:A cross-sectional analysis was performed on 318 microbial surface samples from 28 distinct operational locations in a Class C facility. Colony Forming Unit (CFU) data were analyzed using non-parametric statisticsdue to non-normal distribution, confirmed by Shapiro-Wilk tests on all locations with sufficient sample size (n=12). The Kruskal-Wallis test with Dunn's post-hoc analysis was used for group comparisons. Spearman's correlation was used to assess inter-location relationships.Results:Significant spatial heterogeneity in microbial contamination was confirmed (p<0.0001). Dunn's test identified CP C 11 W as the location with the highest contamination burden (mean CFU=12.17). The most statistically robust contrasts were observed when comparing high-burden sites against the cleanest location, CP C 32 WNme(mean CFU=0.67), which serves as a control benchmark. Multiple high-burden locations, including CP C 11 W and CP C 30 NCu, were found to be significantly more contaminated than this benchmark. No Spearman correlations survived the strict Bonferroni correction; however, the relationship between CP C 11 W and CP C 45 Wif (r=0.882, p<0.05) approached the significance threshold, suggesting a potential pathway requiring further investigation.Conclusions:Microbial contamination within the facility is spatially patterned, not random. The analysis provides a definitive hierarchy of risk, highlighting CP C 11 W as the primary target for enhanced sanitation. While correlational pathways could not be statistically confirmed, near-significant results provide a clear direction for future, more targeted sampling to validate operational links between zones.
Article DOI & Crossmark Data
DOI : https://doi.org/10.22270/ujpr.v10i4.1390
Article Subject Details
Article Keywords Details
- contamination control
- environmental monitoring
- hotspot analysis
- non-parametric statistics
- spatial heterogeneity
- Cleanroom
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