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Applied and Environmental Microbiology, September 2009, p. 5893-5909, Vol. 75, No. 18
0099-2240/09/$08.00+0 doi:10.1128/AEM.02757-08
Copyright © 2009, American Society for Microbiology. All Rights Reserved.
Modeling of Spatially Referenced Environmental and Meteorological Factors Influencing the Probability of Listeria Species Isolation from Natural Environments 
R. Ivanek,1,2*
Y. T. Gröhn,1
M. T. Wells,3
A. J. Lembo Jr.,4,5
B. D. Sauders,6,7 and
M. Wiedmann7
Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York 14853,1 Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas 77843,2 Department of Biological Statistics and Computational Biology, 301 Malott Hall, Cornell University, Ithaca, New York 14853,3 Geography and Geosciences, Salisbury University, Salisbury, Maryland 21804,4 Department of Soil, Crop, and Atmospheric Sciences, 1001 Bradfield Hall, Cornell University, Ithaca, New York 14853,5 New York State Department of Agriculture and Markets, Food Laboratory Division, NYS Office Campus, Building 7A, Albany, New York 12235,6 Department of Food Science, 412 Stocking Hall, Cornell University, Ithaca, New York 148537
Received 4 December 2008/ Accepted 22 July 2009
Many pathogens have the ability to survive and multiply in abiotic environments, representing a possible reservoir and source of human and animal exposure. Our objective was to develop a methodological framework to study spatially explicit environmental and meteorological factors affecting the probability of pathogen isolation from a location. Isolation of Listeria spp. from the natural environment was used as a model system. Logistic regression and classification tree methods were applied, and their predictive performances were compared. Analyses revealed that precipitation and occurrence of alternating freezing and thawing temperatures prior to sample collection, loam soil, water storage to a soil depth of 50 cm, slope gradient, and cardinal direction to the north are key predictors for isolation of Listeria spp. from a spatial location. Different combinations of factors affected the probability of isolation of Listeria spp. from the soil, vegetation, and water layers of a location, indicating that the three layers represent different ecological niches for Listeria spp. The predictive power of classification trees was comparable to that of logistic regression. However, the former were easier to interpret, making them more appealing for field applications. Our study demonstrates how the analysis of a pathogen's spatial distribution improves understanding of the predictors of the pathogen's presence in a particular location and could be used to propose novel control strategies to reduce human and animal environmental exposure.
* Corresponding author. Mailing address: Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843-4458. Phone: (979) 862-4819. Fax: (979) 847-8981. E-mail: rivanek{at}cvm.tamu.edu
Published ahead of print on 31 July 2009.
Applied and Environmental Microbiology, September 2009, p. 5893-5909, Vol. 75, No. 18
0099-2240/09/$08.00+0 doi:10.1128/AEM.02757-08
Copyright © 2009, American Society for Microbiology. All Rights Reserved.
Copyright © 2009 by the American Society for Microbiology. For an alternate route to Journals.ASM.org, visit: http://intl-journals.asm.org | More Info»