POTENTIAL INACCURACY OF MICROBIOLOGICAL COUNTS FROM ROUTINE WATER SAMPLES

The procedures for estimating numbers of organisms in water lead poten tially to large inaccuracies. Routine microbiological sampling is an i mportant component of monitoring source waters for drinking supplies a nd recreational waters. The results should be interpreted with awarene ss that each result is liable to two sorts of error, even when correct procedures are followed. Firstly, there is sampling error due to vari ation over time in microbial density at the place of sampling and, sec ondly, statistical inaccuracies introduced by laboratory methods. Some of the errors can be measured or estimated, especially those in the s econd category. Pre-dilution of a sample, which is unavoidable with he avily contaminated waters, can affect results by chance. For example, if 10 organisms are found after a 100-fold dilution then the estimated count for the original sample would be 1000 with 95% confidence inter vals of 482 - 1834. If a presumptive count is followed up with confirm atory procedures which involve sampling then another imprecision is in troduced. For example, if a presumptive colony count of 25 is checked by confirmatory tests on only 5 colonies then, if 4 of the 5 confirm, the 95% confidence for the final count would be 8 - 24. Although stati stical confidence intervals from the combination of such laboratory pr ocedures could be calculated they have little practical value and coul d cause confusion. An investigator who receives a report in the format of an organism count which is qualified by a 95% confidence interval might wrongly attribute that range to the source water. Variation at t he water source is usually much greater than the errors introduced by proper laboratory procedures. This sample 'error' can be estimated onl y by replicate sampling. All sources of error should be considered whe n the quality of the water is assessed. Decisions about whether the wa ter meets a particular Standard might be better made, from a statistic al point of view, by assessing multiple samples rather than concentrat ing on single counts from very small volumes of water.