Literature DB >> 20477877

Pathogens in water: value and limits of correlation with microbial indicators.

Pierre Payment1, Annie Locas.   

Abstract

This article discusses the value and limitations of using microbial indicators to predict occurrence of enteric pathogens in water. Raw or treated sewage is a primary source of fecal contamination of the receiving surface water or groundwater; hence, understanding the relationship between pathogens and indicators in sewage is an important step in understanding the correlation in receiving waters. This article presents three different datasets representing different concentrations of pathogens and microbial indicators: sewage containing high concentrations of pathogens and indicators, surface water with variable concentrations, and groundwater with low concentrations. In sewage, even with very high levels of microorganisms, no mathematical correlation can predict the type or concentration of any pathogen. After discharge in the environment, direct correlation becomes biologically improbable as dilution, transport, and different inactivation rates occur in various environments. In surface waters, advanced statistical methods such as logistic regression have provided some level of predictability of the occurrence of pathogens but not specific counts. In groundwater, the continuous absence of indicators indicates an improbable occurrence of pathogen. In contrast, when these indicators are detected, pathogen occurrence probability increases significantly. In groundwater, given the nature and dissemination pattern of pathogenic microorganisms, a direct correlation with fecal microbial indicators is not observed and should not be expected. However, the indicators are still useful as a measure of risk. In summary, many pathogens of public health importance do not behave like fecal microbial indicators, and there is still no absolute indicator of their presence, only a probability of their co-occurrence.
Copyright © 2010 The Author(s). Journal compilation © 2010 National Ground Water Association.

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Year:  2011        PMID: 20477877     DOI: 10.1111/j.1745-6584.2010.00710.x

Source DB:  PubMed          Journal:  Ground Water        ISSN: 0017-467X            Impact factor:   2.671


  30 in total

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Authors:  Andrew S Ferguson; Alice C Layton; Brian J Mailloux; Patricia J Culligan; Daniel E Williams; Abby E Smartt; Gary S Sayler; John Feighery; Larry D McKay; Peter S K Knappett; Ekaterina Alexandrova; Talia Arbit; Michael Emch; Veronica Escamilla; Kazi Matin Ahmed; Md Jahangir Alam; P Kim Streatfield; Mohammad Yunus; Alexander van Geen
Journal:  Sci Total Environ       Date:  2012-06-14       Impact factor: 7.963

5.  Occurrence of waterborne pathogens and Escherichia coli at offshore drinking water intakes in lake Ontario.

Authors:  T A Edge; I U H Khan; R Bouchard; J Guo; S Hill; A Locas; L Moore; N Neumann; E Nowak; P Payment; R Yang; R Yerubandi; S Watson
Journal:  Appl Environ Microbiol       Date:  2013-07-08       Impact factor: 4.792

6.  Predicting Salmonella populations from biological, chemical, and physical indicators in Florida surface waters.

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Journal:  Appl Environ Microbiol       Date:  2013-04-26       Impact factor: 4.792

7.  Hand-pumps as reservoirs for microbial contamination of well water.

Authors:  Andrew S Ferguson; Brian J Mailloux; Kazi M Ahmed; Alexander van Geen; Larry D McKay; Patricia J Culligan
Journal:  J Water Health       Date:  2011-12       Impact factor: 1.744

8.  Abilities of the mCP Agar method and CRENAME alpha toxin-specific real-time PCR assay to detect Clostridium perfringens spores in drinking water.

Authors:  Andrée F Maheux; Eve Bérubé; Dominique K Boudreau; Romain Villéger; Philippe Cantin; Maurice Boissinot; Luc Bissonnette; Michel G Bergeron
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9.  Alternative indicators for monitoring Cryptosporidium oocysts in reclaimed water.

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Journal:  Environ Sci Pollut Res Int       Date:  2012-12-18       Impact factor: 4.223

10.  Exposure factors for wastewater-irrigated Asian vegetables and a probabilistic rotavirus disease burden model for their consumption.

Authors:  Hoi-Fei Mok; Andrew J Hamilton
Journal:  Risk Anal       Date:  2014-02-27       Impact factor: 4.000

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