Principal component analysis in long term assessment of total viable plate count of municipal water distribution network system in healthcare facility

Yıl 2022, Cilt: 5 Sayı: 2, 165 - 171, 30.06.2022

Mostafa Eissa Engy Rashed Dalia Eissa

https://doi.org/10.35208/ert.1062683

Cited By: 1

Öz

The microbial quality of water is a critical safety aspect that should not be overlooked, especially when considering human consumption in the facilities for healthcare and the treatment of health compromised populations. The present work aimed to study a municipal network for city water within a healthcare facility microbiologically. The implementation of multivariate analysis was conducted over collected data to decipher trends of the microbiological count of samples from different points-of-use. The statistical study involved an Eigenvalue determination, score graph, loading plot study and outlier diagram. Data showed clustering tendency with aberrant values could be observed. The first component appeared to be associated with bioburden density in the water. While the other component showed a link to the relative locations of the distribution points in the facility and the length of the water lines from the source feeding city water to a great extent. The two components explained more than 55% of the variations in data. A property that highlighted a strong agreement between the order of points-of-use in the loading plot with that of ratio factor which was obtained from the Total Viable Count over the hypothetical distance of sampling port from the reference feeding entrance. Thus, there was evidence of variation in the microbial quality affected by the biological stability of the water distribution system that needed attention and an improvement plan for better control of microbial content in city water to prevent possible excursions in the future. The study showed a valuable perspective approach for the quantitative examination of the microbiological stability of the municipal water distribution network system.

Anahtar Kelimeler

Eigen value, loading plot, outlier diagram, PCA, score graph, scree plot

Kaynakça

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