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Summary Molecular typing methods have become a common part of the surveillance of foodborne pathogens. In particular, pulsed-field gel electrophoresis (PFGE) has been used successfully to identify outbreaks of Escherichia coli O157:H7 in humans from a variety of food and environmental sources. However, some PFGE patterns appear commonly in surveillance systems, making it more difficult to distinguish between outbreak and sporadic cases based on molecular data alone. In addition, it is unknown whether these common patterns might have unique epidemiological characteristics reflected in their spatial and temporal distributions. Using E. coli O157:H7 surveillance data from Alberta, collected from 2000 to 2002, we investigated whether E. coli O157:H7 with provincial PFGE pattern 8 (national designation ECXAI.0001) clustered in space, time and space–time relative to other PFGE patterns using the spatial scan statistic. Based on our purely spatial and temporal scans using a Bernoulli model, there did not appear to be strong evidence that isolates of E. coli O157:H7 with provincial PFGE pattern 8 are distributed differently from other PFGE patterns. However, we did identify space–time clusters of isolates with PFGE pattern 8, using a Bernoulli model and a space–time permutation model, which included known outbreaks and potentially unrecognized outbreaks or additional outbreak cases. There were differences between the two models in the space–time clusters identified, which suggests that the use of both models could increase the sensitivity of a quantitative surveillance system for identifying outbreaks involving isolates sharing a common PFGE pattern.

Summary Exposure to microorganisms resistant to antimicrobials may constitute a health risk to human populations. It is believed that one route of exposure occurs when people engage in recreational activities in water contaminated with these microorganisms. The main objective of this study was to explore population-level and environmental determinants specifically associated with the presence of antimicrobial resistant (AMR) generic Escherichia coli isolated from recreational waters sampled from beaches located in southern Quebec, Canada. Water samples originated from the Quebec provincial beach surveillance program for the summers of 2004 and 2005. This study focused on three classes of determinants, namely: agricultural, population-level and beach characteristics for a total of 19 specific factors. The study was designed as a retrospective observational analysis and factors were assessed using logistic regression methods. From the multivariable analysis, the data suggested that the percentage of land used for spreading liquid manure was a significant factor associated with the presence of AMR E. coli (OR = 27.73). Conceptually, broad factors potentially influencing the presence of AMR bacteria in water must be assessed specifically in addition to factors associated with general microbial contamination. Presence of AMR E. coli in recreational waters from beaches in southern Quebec may represent a risk for people engaging in water activities and this study provides preliminary evidence that agricultural practices, specifically spreading liquid manure in agricultural lands nearby beaches, may be linked to the contamination of these waters by AMR E. coli.

Using negative binomial and multi-level Poisson models, the authors determined the statistical significance of agricultural and socio-economic risk factors for rates of reported disease associated with Escherichia coli O157 in census subdivisions (CSDs) in Alberta, Canada, 2000-2002. Variables relating to population stability, aboriginal composition of the CSDs, and the economic relationship between CSDs and urban centres were significant risk factors. The percentage of individuals living in low-income households was not a statistically significant risk factor for rates of disease. The statistical significance of cattle density, recorded at a higher geographical level, depended on the method used to correct for overdispersion, the number of levels included in the multi-level models, and the choice of using all reported cases or only sporadic cases. Our results highlight the importance of local socio-economic risk factors in determining rates of disease associated with E. coli O157, but their relationship with individual risk factors requires further evaluation.