Are microbial indicators and pathogens correlated? A statistical analysis of 40 years of research
Author(s) -
Jianyong Wu,
S. C. Long,
Debalina Das,
Sarah Dorner
Publication year - 2011
Publication title -
journal of water and health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.482
H-Index - 59
eISSN - 1996-7829
pISSN - 1477-8920
DOI - 10.2166/wh.2011.117
Subject(s) - clostridium perfringens , pathogen , biology , indicator organism , fecal coliform , logistic regression , statistical analysis , indicator bacteria , veterinary medicine , ecology , statistics , microbiology and biotechnology , water quality , medicine , mathematics , bacteria , genetics
Indicator organisms are used to assess public health risk in recreational waters, to highlight periods of challenge to drinking water treatment plants, and to determine the effectiveness of treatment and the quality of distributed water. However, many have questioned their efficacy for indicating pathogen risk. Five hundred and forty cases representing independent indicator-pathogen correlations were obtained from the literature for the period 1970-2009. The data were analyzed to assess factors affecting correlations using a logistic regression model considering indicator classes, pathogen classes, water types, pathogen sources, sample size, the number of samples with pathogens, the detection method, year of publication and statistical methods. Although no single indicator was identified as the most correlated with pathogens, coliphages, F-specific coliphages, Clostridium perfringens, fecal streptococci and total coliforms were more likely than other indicators to be correlated with pathogens. The most important factors in determining correlations between indicator-pathogen pairs were the sample size and the number of samples positive for pathogens. Pathogen sources, detection methods and other variables have little influence on correlations between indicators and pathogens. Results suggest that much of the controversy with regards to indicator and pathogen correlations is the result of studies with insufficient data for assessing correlations.
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