Bioburden Analysis and Microbiological Stability of Municipal Distribution System through Examination of Transformed Total Microbial Count Dataset | ||||
| Frontiers in Scientific Research and Technology | ||||
| Volume 8, Issue 1, February 2024 PDF (653.92 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/fsrt.2023.251967.1115 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Mostafa Eissa 
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| Pharmaceutical Research Facility, Cairo, Egypt | ||||
| Abstract | ||||
| The availability of water suitable for human consumption has become an increasingly critical challenge that humanity faces in the modern period after witnessing dramatic climate changes. Public health authorities in every nation bear the responsibility of monitoring and controlling the quality of fulfilling requests from the community for potable water through valid and stable distribution infrastructure. In this study, a parametric statistical assessment was focused on the microbiological quality of city water in a specific section of the municipal water network that supplies a healthcare plant. The examination period covers a one-year duration of collecting qualitative and quantitative testing results. Non-normal microbial count datasets were logarithmically transformed and investigated through the application of a normal probability plot at 95% Confidence Interval (CI). Despite the absence of Out-Of-Specification (OOS) results, the municipal distribution system showed significant variations between its sections suggesting heterogeneity between the investigated segments in the bioburden. However, an initial exploratory Laney attribute control chart did not demonstrate any Out-Of-Control (OOC) points. Nevertheless, a significant variation was evident using One-Way ANOVA (at α 0.05) combined with the Pareto plot and residual analysis. There was a significant difference in the microbiological density in water between different municipal distribution sections with most points of use showing a strong association with each other in bioburden count. The transformation enabled the use of statistical test tools to detect the distribution system efficacy and mark the microbiological instability within the network. | ||||
| Keywords | ||||
| Laney Attribute Chart; Normal Probability Plot; Correlation Matrix; Residuals Plot; Pareto Plot | ||||
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