Quantitative microbiological risk assessment requires quantitative data to assess consumer exposure to pathogens and the resulting health risk. The aim of this study was to evaluate data sets on the occurrence of Cryptosporidium oocysts in raw water and on the removal of model organisms (anaerobic spores, bacteriophages) to perform such a risk assessment. A tiered approach was used by first calculating approximate point estimates and when the point estimate was close to the required safety level (10(4) annual risk of infection), fitting the data to probability distributions and Monte Carlo analysis to calculate the distribution of the risk of infection. Sensitivity analysis showed that the variability in the Cryptosporidium data in raw water (largely introduced by the variability of the recovery efficiency of the detection method) determined most of the variance in the risk estimate.