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Statistical Approaches for Modeling in Microbial Source Tracking

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Microbial Source Tracking: Methods, Applications, and Case Studies

Abstract

Microbial source tracking (MST) concerns the definition of new indicators and appropriate detection methods, the identification of host-specific indicators of fecal pollution, and ultimately the development of useful and reliable predictive models for practical deployment. Optimal predictive models should be designed using proper statistical and computational tools for the analysis of the available data samples. A further requirement is found in the determination of appropriate sets of predictors (indicators, tracers) for developing accurate and low-cost MST solutions. This chapter briefly reviews some of these modeling tools, and their use and feasibility in providing more accurate MST-based results. It also evaluates the potential of established and new algorithmic methods to the identification of fecal pollution sources.

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Authors and Affiliations

  1. Department of Microbiology, University of Barcelona, Avda. Diagonal 645, Barcelona, Spain

    Anicet R. Blanch

Authors
  1. Lluís A. Belanche
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  2. Anicet R. Blanch
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Correspondence to Anicet R. Blanch .

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Editors and Affiliations

  1. Dept. Crop & Soil Environmental Sciences, Virginia Tech, Prince Hall 401, Blacksburg, 24061, Virgin Islands, USA

    Charles Hagedorn

  2. Fac. Biologia, Depto. Microbiologia, Universitat Barcelona, Avenida Diagonal 645, Barcelona, 08028, Spain

    Anicet R. Blanch

  3. Dept. Biology, Div. Integrative Biology (IB), University of South Florida, E. Fowler Ave. 4202, Tampa, 33620, Florida, USA

    Valerie J. Harwood

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Belanche, L.A., Blanch, A.R. (2011). Statistical Approaches for Modeling in Microbial Source Tracking. In: Hagedorn, C., Blanch, A., Harwood, V. (eds) Microbial Source Tracking: Methods, Applications, and Case Studies. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9386-1_9

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