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Background: Current guidelines recommend the use of Escherichia coli (EC) or thermotolerant ("fecal") coliforms (FC) as indicators of fecal contamination in drinking water. Despite their broad use as measures of water quality, there remains limited evidence for an association between EC or FC and diarrheal illness: a previous review found no evidence for a link between diarrhea and these indicators in household drinking water., Objectives: We conducted a systematic review and meta-analysis to update the results of the previous review with newly available evidence, to explore differences between EC and FC indicators, and to assess the quality of available evidence., Methods: We searched major databases using broad terms for household water quality and diarrhea. We extracted study characteristics and relative risks (RR) from relevant studies. We pooled RRs using random effects models with inverse variance weighting, and used standard methods to evaluate heterogeneity and publication bias., Results: We identified 20 relevant studies; 14 studies provided extractable results for meta-analysis. When combining all studies, we found no association between EC or FC and diarrhea (RR 1.26 [95% CI: 0.98, 1.63]). When analyzing EC and FC separately, we found evidence for an association between diarrhea and EC (RR: 1.54 [95% CI: 1.37, 1.74]) but not FC (RR: 1.07 [95% CI: 0.79, 1.45]). Across all studies, we identified several elements of study design and reporting (e.g., timing of outcome and exposure measurement, accounting for correlated outcomes) that could be improved upon in future studies that evaluate the association between drinking water contamination and health., Conclusions: Our findings, based on a review of the published literature, suggest that these two coliform groups have different associations with diarrhea in household drinking water. Our results support the use of EC as a fecal indicator in household drinking water.

Background: Studies of health risks associated with recreational water exposure require investigators to make choices about water quality indicator averaging techniques, exposure definitions, follow-up periods, and model specifications; however, investigators seldom describe the impact of these choices on reported results. Our objectives are to report illness risk from swimming at a marine beach affected by nonpoint sources of urban runoff, measure associations between fecal indicator bacteria levels and subsequent illness among swimmers, and investigate the sensitivity of results to a range of exposure and outcome definitions., Methods: In 2009, we enrolled 5674 people in a prospective cohort at Malibu Beach, a coastal marine beach in California, and measured daily health symptoms 10-19 days later. Concurrent water quality samples were analyzed for indicator bacteria using culture and molecular methods. We compared illness risk between nonswimmers and swimmers, and among swimmers exposed to various levels of fecal indicator bacteria., Results: Diarrhea was more common among swimmers than nonswimmers (adjusted odds ratio = 1.88 [95% confidence interval = 1.09-3.24]) within 3 days of the beach visit. Water quality was generally good (fecal indicator bacteria levels exceeded water quality guidelines for only 7% of study samples). Fecal indicator bacteria levels were not consistently associated with swimmer illness. Sensitivity analyses demonstrated that overall inference was not substantially affected by the choice of exposure and outcome definitions., Conclusions: This study suggests that the 3 days following a beach visit may be the most relevant period for health outcome measurement in recreational water studies. Under the water quality conditions observed in this study, fecal indicator bacteria levels were not associated with swimmer illness.

In collaboration with a local non-profit organization, this study evaluated the expansion of a program that promoted and installed Mesita Azul, an ultraviolet-disinfection system designed to treat household drinking water in rural Mexico. We conducted a 15-month, cluster-randomized stepped wedge trial by randomizing the order in which 24 communities (444 households) received the intervention. We measured primary outcomes (water contamination and diarrhea) during seven household visits. The intervention increased the percentage of households with access to treated and safely stored drinking water (23-62%), and reduced the percentage of households with Escherichia coli contaminated drinking water (risk difference (RD): -19% [95% CI: -27%, -14%]). No significant reduction in diarrhea was observed (RD: -0.1% [95% CI: -1.1%, 0.9%]). We conclude that household water quality improvements measured in this study justify future promotion of the Mesita Azul, and that future studies to measure its health impact would be valuable if conducted in populations with higher diarrhea prevalence.

Complier average causal effects (CACE) estimate the impact of an intervention among treatment compliers in randomized trials. Methods used to estimate CACE have been outlined for parallel-arm trials (e.g., using an instrumental variables (IV) estimator) but not for other randomized study designs. Here, we propose a method for estimating CACE in randomized stepped wedge trials, where experimental units cross over from control conditions to intervention conditions in a randomized sequence. We illustrate the approach with a cluster-randomized drinking water trial conducted in rural Mexico from 2009 to 2011. Additionally, we evaluated the plausibility of assumptions required to estimate CACE using the IV approach, which are testable in stepped wedge trials but not in parallel-arm trials. We observed small increases in the magnitude of CACE risk differences compared with intention-to-treat estimates for drinking water contamination (risk difference (RD) = -22% (95% confidence interval (CI): -33, -11) vs. RD = -19% (95% CI: -26, -12)) and diarrhea (RD = -0.8% (95% CI: -2.1, 0.4) vs. RD = -0.1% (95% CI: -1.1, 0.9)). Assumptions required for IV analysis were probably violated. Stepped wedge trials allow investigators to estimate CACE with an approach that avoids the stronger assumptions required for CACE estimation in parallel-arm trials. Inclusion of CACE estimates in stepped wedge trials with imperfect compliance could enhance reporting and interpretation of the results of such trials.

Abstract: Background: Traditional fecal indicator bacteria (FIB) measurement is too slow (>18 h) for timely swimmer warnings. Objectives: Assess relationship of rapid indicator methods (qPCR) to illness at a marine beach impacted by urban runoff. Methods: We measured baseline and two-week health in 9525 individuals visiting Doheny Beach 2007–08. Illness rates were compared (swimmers vs. non-swimmers). FIB measured by traditional (Enterococcus spp. by EPA Method 1600 or Enterolert™, fecal coliforms, total coliforms) and three rapid qPCR assays for Enterococcus spp. (Taqman, Scorpion-1, Scorpion-2) were compared to health. Primary bacterial source was a creek flowing untreated into ocean; the creek did not reach the ocean when a sand berm formed. This provided a natural experiment for examining FIB-health relationships under varying conditions. Results: We observed significant increases in diarrhea (OR 1.90, 95% CI 1.29–2.80 for swallowing water) and other outcomes in swimmers compared to non-swimmers. Exposure (body immersion, head immersion, swallowed water) was associated with increasing risk of gastrointestinal illness (GI). Daily GI incidence patterns were different: swimmers (2-day peak) and non-swimmers (no peak). With berm-open, we observed associations between GI and traditional and rapid methods for Enterococcus; fewer associations occurred when berm status was not considered. Conclusions: We found increased risk of GI at this urban runoff beach. When FIB source flowed freely (berm-open), several traditional and rapid indicators were related to illness. When FIB source was weak (berm-closed) fewer illness associations were seen. These different relationships under different conditions at a single beach demonstrate the difficulties using these indicators to predict health risk. [Copyright &y& Elsevier]