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The use of randomization tests to assess the degree of similarity in PFGE patterns of E. coli O157 isolates from known outbreaks and statistical space–time clusters

Published online by Cambridge University Press:  02 June 2006

D. L. PEARL ,
M. LOUIE ,
L. CHUI ,
K. DORÉ ,
K. M. GRIMSRUD ,
S. W. MARTIN ,
P. MICHEL ,
L. W. SVENSON  and
S. A. McEWEN
D. L. PEARL
Affiliation:
Department of Population Medicine, University of Guelph, Guelph, Ontario, Canada
M. LOUIE
Affiliation:
Provincial Laboratory for Public Health (Microbiology), Calgary, Alberta, Canada
L. CHUI
Affiliation:
Provincial Laboratory for Public Health (Microbiology), Edmonton, Alberta, Canada
K. DORÉ
Affiliation:
Foodborne, Waterborne and Zoonotic Infections Division, Public Health Agency of Canada, Guelph, Ontario, Canada
K. M. GRIMSRUD
Affiliation:
Alberta Health and Wellness, Edmonton, Alberta, Canada
S. W. MARTIN
Affiliation:
Department of Population Medicine, University of Guelph, Guelph, Ontario, Canada
P. MICHEL
Affiliation:
Laboratory for Foodborne Zoonoses, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada
L. W. SVENSON
Affiliation:
Alberta Health and Wellness, Edmonton, Alberta, Canada
S. A. McEWEN
Affiliation:
Department of Population Medicine, University of Guelph, Guelph, Ontario, Canada
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Abstract

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Using isolates from reported cases of Escherichia coli O157 from Alberta, Canada in 2002, we applied randomization tests to determine if cases associated with an outbreak or statistical space–time cluster had more similar pulsed-field gel electrophoresis patterns, based on Dice coefficients, than expected by chance alone. Within each outbreak and space–time cluster, we assessed the mean, median, 25th percentile, 75th percentile, standard deviation, coefficient of variation, and interquartile range of the Dice coefficients of each pairwise comparison among the isolates. To assess the statistical significance of measures of location (e.g. mean) and variation (e.g. standard deviation) we created randomization distributions using all isolates or only isolates from sporadic cases. We determined that randomization tests are an appropriate tool for evaluating the similarity among isolates from cases that have been linked epidemiologically or statistically. We found little difference between using all cases or only sporadic cases when creating our randomization distributions.

Type
Research Article
Information
Epidemiology & Infection , Volume 135 , Issue 1 , January 2007 , pp. 100 - 109
Copyright
© 2006 Cambridge University Press