首页> 美国卫生研究院文献>International Journal of Environmental Research and Public Health >Fecal Indicator Bacteria Data to Characterize Drinking Water Quality in Low-Resource Settings: Summary of Current Practices and Recommendations for Improving Validity
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Fecal Indicator Bacteria Data to Characterize Drinking Water Quality in Low-Resource Settings: Summary of Current Practices and Recommendations for Improving Validity

机译:粪便指标细菌数据在低资源环境中表征饮用水质量:当前做法和提高有效性的建议摘要

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摘要

Fecal indicator bacteria (FIB) values are widely used to assess microbial contamination in drinking water and to advance the modeling of infectious disease risks. The membrane filtration (MF) testing technique for FIB is widely adapted for use in low- and middle-income countries (LMICs). We conducted a systematic literature review on the use of MF-based FIB data in LMICs and summarized statistical methods from 172 articles. We then applied the commonly used statistical methods from the review on publicly available datasets to illustrate how data analysis methods affect FIB results and interpretation. Our findings indicate that standard methods for processing samples are not widely reported, the selection of statistical tests is rarely justified, and, depending on the application, statistical methods can change risk perception and present misleading results. These results raise concerns about the validity of FIB data collection, analysis, and presentation in LMICs. To improve evidence quality, we propose a FIB data reporting checklist to use as a reminder for researchers and practitioners.
机译:粪便指标细菌(FIB)值广泛用于评估饮用水中的微生物污染,并推进传染病风险的建模。 FIB的膜过滤(MF)测试技术广泛适用于低收入和中等收入国家(LMIC)。我们对使用基于MF的FIB数据进行了系统的文献综述,从172篇文章中汇总统计方法。然后,我们将常用的统计方法应用于公开可用数据集的审查中,以说明数据分析方法如何影响FIB结果和解释。我们的研究结果表明,处理样品的标准方法并未被广泛报道,统计测试的选择很少有理,并且根据申请,统计方法可以改变风险感知和目前误导性结果。这些结果提高了对LMIC中的FIB数据收集,分析和演示文稿的有效性的担忧。为了提高证据质量,我们提出了一个FIB数据报告清单,以便用于研究人员和从业者的提醒。

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