On the use of total aerobic spore bacteria to make treatment decisions due to Cryptosporidium risk at public water system wells.

Spore reduction can be used as a surrogate measure of Cryptosporidium natural filtration efficiency. Estimates of log10 (log) reduction were derived from spore measurements in paired surface and well water samples in Casper Wyoming and Kearney Nebraska. We found that these data were suitable for testing the hypothesis (H0) that the average reduction at each site was 2 log or less, using a one-sided Student's t-test. After establishing data quality objectives for the test (expressed as tolerable Type I and Type II error rates), we evaluated the test's performance as a function of the (a) true log reduction, (b) number of paired samples assayed and (c) variance of observed log reductions. We found that 36 paired spore samples are sufficient to achieve the objectives over a wide range of variance, including the variances observed in the two data sets. We also explored the feasibility of using smaller numbers of paired spore samples to supplement bioparticle counts for screening purposes in alluvial aquifers, to differentiate wells with large volume surface water induced recharge from wells with negligible surface water induced recharge. With key assumptions, we propose a normal statistical test of the same hypothesis (H0), but with different performance objectives. As few as six paired spore samples appear adequate as a screening metric to supplement bioparticle counts to differentiate wells in alluvial aquifers with large volume surface water induced recharge. For the case when all available information (including failure to reject H0 based on the limited paired spore data) leads to the conclusion that wells have large surface water induced recharge, we recommend further evaluation using additional paired biweekly spore samples.

Total coliform and E. coli in public water systems using undisinfected ground water in the United States.

Public water systems (PWSs) in the United States generate total coliform (TC) and Escherichia coli (EC) monitoring data, as required by the Total Coliform Rule (TCR). We analyzed data generated in 2011 by approximately 38,000 small (serving fewer than 4101 individuals) undisinfected public water systems (PWSs). We used statistical modeling to characterize a distribution of TC detection probabilities for each of nine groupings of PWSs based on system type (community, non-transient non-community, and transient non-community) and population served (less than 101, 101-1000 and 1001-4100 people). We found that among PWS types sampled in 2011, on average, undisinfected transient PWSs test positive for TC 4.3% of the time as compared with 3% for undisinfected non-transient PWSs and 2.5% for undisinfected community PWSs. Within each type of PWS, the smaller systems have higher median TC detection than the larger systems. All TC-positive samples were assayed for EC. Among TC-positive samples from small undisinfected PWSs, EC is detected in about 5% of samples, regardless of PWS type or size. We evaluated the upper tail of the TC detection probability distributions and found that significant percentages of some system types have high TC detection probabilities. For example, assuming the systems providing data are nationally-representative, then 5.0% of the ∼50,000 small undisinfected transient PWSs in the U.S. have TC detection probabilities of 20% or more. Communities with such high TC detection probabilities may have elevated risk of acute gastrointestinal (AGI) illness - perhaps as great or greater than the attributable risk to drinking water (6-22%) calculated for 14 Wisconsin community PWSs with much lower TC detection probabilities (about 2.3%, Borchardt et al., 2012).

Cryptosporidium Infection Risk: Results of New Dose-Response Modeling.

Cryptosporidium human dose-response data from seven species/isolates are used to investigate six models of varying complexity that estimate infection probability as a function of dose. Previous models attempt to explicitly account for virulence differences among C. parvum isolates, using three or six species/isolates. Four (two new) models assume species/isolate differences are insignificant and three of these (all but exponential) allow for variable human susceptibility. These three human-focused models (fractional Poisson, exponential with immunity and beta-Poisson) are relatively simple yet fit the data significantly better than the more complex isolate-focused models. Among these three, the one-parameter fractional Poisson model is the simplest but assumes that all Cryptosporidium oocysts used in the studies were capable of initiating infection. The exponential with immunity model does not require such an assumption and includes the fractional Poisson as a special case. The fractional Poisson model is an upper bound of the exponential with immunity model and applies when all oocysts are capable of initiating infection. The beta Poisson model does not allow an immune human subpopulation; thus infection probability approaches 100% as dose becomes huge. All three of these models predict significantly (>10x) greater risk at the low doses that consumers might receive if exposed through drinking water or other environmental exposure (e.g., 72% vs. 4% infection probability for a one oocyst dose) than previously predicted. This new insight into Cryptosporidium risk suggests additional inactivation and removal via treatment may be needed to meet any specified risk target, such as a suggested 10-4 annual risk of Cryptosporidium infection.

Fractional poisson--a simple dose-response model for human norovirus.

This study utilizes old and new Norovirus (NoV) human challenge data to model the dose-response relationship for human NoV infection. The combined data set is used to update estimates from a previously published beta-Poisson dose-response model that includes parameters for virus aggregation and for a beta-distribution that describes variable susceptibility among hosts. The quality of the beta-Poisson model is examined and a simpler model is proposed. The new model (fractional Poisson) characterizes hosts as either perfectly susceptible or perfectly immune, requiring a single parameter (the fraction of perfectly susceptible hosts) in place of the two-parameter beta-distribution. A second parameter is included to account for virus aggregation in the same fashion as it is added to the beta-Poisson model. Infection probability is simply the product of the probability of nonzero exposure (at least one virus or aggregate is ingested) and the fraction of susceptible hosts. The model is computationally simple and appears to be well suited to the data from the NoV human challenge studies. The model's deviance is similar to that of the beta-Poisson, but with one parameter, rather than two. As a result, the Akaike information criterion favors the fractional Poisson over the beta-Poisson model. At low, environmentally relevant exposure levels (<100), estimation error is small for the fractional Poisson model; however, caution is advised because no subjects were challenged at such a low dose. New low-dose data would be of great value to further clarify the NoV dose-response relationship and to support improved risk assessment for environmentally relevant exposures.