Effect of unboiled water consumption data on sensitivity analysis in quantitative microbial risk assessment

Quantitative microbial risk assessment of drinking water is generally followed by sensitivity analysis for examining the relative importance of variables of the simulation model on the outcome. This study investigated the effect of the statistical methods applied to unboiled water consumption data on sensitivity analysis. The sensitivity analysis for concentration of Escherichia coli (E. coli) in treated water showed completely different results from the analysis for E. coli dose. This was due to the application of a Poisson model to the water consumption, which suggested that 27% of the people did not drink tap water. Our study then applied a different model—an exponential distribution—to the water consumption data. In addition, incidental water intake was assigned to non-consumers in the Poisson model. The results of sensitivity analyses for these cases were very different from the ones obtained from the first analysis. This study therefore demonstrated that the statistical methods used to analyze water consumption data have great impacts on sensitivity analysis, although they do not affect the yearly risk of infection. Specifically, statistical methods may devalue sensitivity analysis. To avoid this problem, it is preferable to apply a continuous model such as the exponential model, rather than a discrete one such as the Poisson model, to describe the variability in water consumption