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Waterborne transmission of Cryptosporidium parvum is well-established as a source in outbreaks of cryptosporidiosis; however, the role of tap water in endemic disease is unclear. The authors applied a risk assessment approach incorporating uncertainty analysis to examine the potential role of tap water in the transmission of endemic C. parvum infection. The model had two components: exposure-infection, to relate low-dose exposure to infection; and infection-outcome, to include the probabilities of clinical outcomes leading to case detection and reporting. The population was divided into four subgroups: adults and children with and without acquired immunodeficiency syndrome (AIDS). Because of the high degree of uncertainty associated with available measures, a plausible baseline concentration of oocysts, 1 per 1,000 liters, was assumed for input to the model. In the non-AIDS subgroups, the predicted median annual risk of infection was approximately 1 in 1,000 (non-AIDS adults: 0.0009 infection/person/year, 95% confidence interval (CI) 0.0003-0.0028), while in the AIDS subgroups the predicted risk was 2 in 1,000 (AIDS adults: 0.0019 infection/person/year, 95% CI 0.0003-0.0130). When the risks were applied to the 1995 New York City population, more than 6,000 infections were estimated, with 99% occurring in the non-AIDS categories. Estimates of the overall probabilities that an infection would result in a reported case predicted that three reported illnesses would occur out of every 10,000 infections in non-AIDS adults (95% CI 5 x 10[-5] to 2 x 10[-3]), with a 10-fold higher probability in the non-AIDS pediatric subgroup. In contrast, the majority of infections occurring in the AIDS subgroup were predicted to result in reported cases (AIDS adults: probability = 0.61, 95% CI 0.39-0.80). When the model was applied to the New York City population, the calculated number of tap-water-related cases per year in the non-AIDS subgroups was six (95% CI 1-29), and in the AIDS subgroups it was 34 (95% CI 6-240).

Cryptosporidium in Tap Water: Comparison of Predicted Risks with Observed Levels of Disease