Rapid assessment of drinking-water quality in the - WHO/UNICEF ...

condition, devices, and practices in the water-supply system that pose an actual or potential danger to
drinking-water quality, and thus to the health and well-being of the consumers. The most effective way to
undertake sanitary inspections is a semiquantitative, standardized approach using logical questions and a
simple scoring system. Sanitary inspections complement water-quality analyses by providing a longerterm
perspective on the risks of microbiological contamination, rather than the “snapshot” view of waterquality
analyses, and there is an increase in the power of analysis when both types of data are available.
In the RADWQ survey in Jordan, special questionnaires were used in the sanitary inspections of all water
supplies (Annex 9). The questionnaires comprised sets of 10 questions with only “yes” or “no” responses
allowed, which enabled the interviewer to quickly and easily mark the answer. Sanitary inspection scores
were then derived from the results of the sanitary inspections.
Risk-to-health analysis
A relative health risk for a water supply can be calculated by combining the sanitary inspection score with
data on thermotolerant coliform counts (e.g. see Table 3.18). The sanitary inspections provide a longerterm
perspective on the risks of microbiological contamination, while the coliform data privide more of a
“snapshot” of current conditions. Ranking water supplies in such a way allows interventions aimed at
improving water safety to be prioritized, and supports effective and rational decision-making.
Analysis of proxy parameters
The purpose of a proxy analysis in RADWQ surveys is to quantify correlations between pairs of selected
water-quality parameters, and determine if one parameter could be used to approximate the result that
would be given by the direct measurement of a second parameter (which might be more difficult,
expensive or time-consuming to measure). Most commonly, a proxy analysis is used to investigate the
correlations between:
faecal contamination (measured as the thermotolerant coliform count) and turbidity;
thermotolerant coliform count and faecal streptococci level; and
conductivity and nitrate, fluoride or arsenic.
The strength of association between two water-quality parameters in RADWQ surveys is measured by
calculating Pearson’s r, a linear correlation coefficient. If the paired data lie exactly along a straight line
with a positive slope, then r = 1; if they lie exactly along a straight line with a negative slope, r = -1; and
if there is no correlation, then r = 0. The main limitations of Pearson’s r are that the method assumes a
linear association between two variables, and would not approximate well a non-linear relationship; it
assumes the data are distributed normally; and the value of r is disproportionately influenced by outlier
data. The justifications for using Pearson’s r are that it can be easily calculated in Microsoft’s Excel
spreadsheet, and that the snapshot nature of RADWQ surveys does not justify using a more complicated
analysis, such as Spearman’s rho.
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