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Microbial Source Tracking Study

Performance, Design, and Analysis in Microbial Source Tracking Studies

Donald M. Stoeckel1 and Valerie J. Harwood2*

U.S. Geological Survey, Ohio Water Science Center, Columbus, OH1; Department of Biology, University of South Florida, Tampa, FL2

* Mailing address:  Department of Biology, University of South Florida, Tampa, FL 33620.  Phone: (813) 974-1524. Fax: (813) 974-3263. E-mail:

Published in Applied and Environmental Microbiology, v. 73, p. 2405-2415.

Article Full Text

Abstract (the publication contains no abstract)

Understanding the source or sources of fecal pollution to environmental waters is essential for effective protection of public health, for remediation of contaminated waters, and for regulatory tasks such as establishing total maximum daily loads (TMDLs). Human-health-related regulatory standards for water quality are based on indicator-bacteria concentrations; yet, these organisms are shed in the feces of a wide variety of warm-blooded animals. Various methodologies, collectively termed microbial source tracking (MST), have been applied to the question of fecal source determination.  The development, validation, and implementation of these methods varies widely among studies and practitioners. This review provides comparative performance characteristics for various MST methods, with particular emphasis on accuracy. Method comparisons can be confounded by the use of different levels of source discrimination (k), e.g., an animal-human split vs. a species-level split (such as dog-cow-goose-human). A novel measure, called the benefit over random (BOR), is used to compare classification accuracy across studies corrected for different levels of k . Performance measures that contribute to understanding of method classification accuracy include positive and negative predictive value, sensitivity, and specificity, each of which should be based on samples collected independently of method-development samples or library isolates. Sensitivity and specificity, calculated from previously published laboratory data for various MST studies, are tabulated and discussed, as are strategies to control error at the next level of application (field studies).


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