Receiver-operating characteristics analysis: a new approach to predicting the presence of pathogens in surface waters.

Environ Sci Technol

Division of Environmental and Occupational Health Sciences, University of Illinois at Chicago School of Public Health, 2121 West Taylor Street, M/C 922, Chicago, Illinois 60612, United States.

Published: May 2014

Fecal indicator microbes are used to monitor the public health risks of recreating in surface waters. However, the importance of indicator tests as predictors of waterborne pathogens has been unclear. Numerous studies have also shown that the survival and growth of indicator organisms may depend on location-specific factors that cannot be broadly generalized. We used receiver-operating characteristic (ROC) methods to determine whether fecal indicator species are capable of predicting the presence of Giardia and Cryptosporidium in fresh surface waters in the Chicago area. We also derived recreational water quality criteria specific to our location with respect to this end point. We considered five fecal indicators: enterococci measured by culture and quantitative polymerase chain reaction (qPCR), Escherichia coli measured by culture, somatic coliphage, and F+ coliphage. All fecal indicators were found to predict the presence and absence of protozoan pathogens. The test for enterococci measured by culture was the poorest predictor of the presence of pathogens. The test for enterococci measured by qPCR was the best predictor of the presence of Giardia, but not an important predictor of the presence of Cryptosporidium. The test for somatic coliphage was a relatively strong predictor of the presence of both pathogens. This analysis supports the use of qPCR-based assays over culture-based assays for predicting the presence of Giardia in fresh surface water. Our criteria were optimized for the prediction of the presence of Giardia and Cryptosporidium in our location and were closely aligned with criteria of the U.S. Environmental Protection Agency derived from epidemiological risk assessment. The ROC approach is flexible and can inform location-specific interpretation of water quality monitoring data and decision making.

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http://dx.doi.org/10.1021/es4047044DOI Listing

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