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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. [ABSTRACT FROM AUTHOR]

To determine whether drinking water contaminated with antimicrobial-resistant E. coli is associated with the carriage of resistant E. coli, selected households sending water samples to Ontario and Alberta laboratories in 2005-2006 were asked to participate in a cross-sectional study. Household members aged ≥12 years were asked to complete a questionnaire and to submit a rectal swab. In 878 individuals, 41% carried a resistant strain of E. coli and 28% carried a multidrug-resistant strain. The risk of carriage of resistant E. coli was 1·26 times higher for users of water contaminated with resistant E. coli. Other risk factors included international travel [prevalence ratio (PR) 1·33], having a child in nappies (PR 1·33), being male (PR 1·33), and frequent handling of raw red meats (PR 1·10). Protecting private water sources (e.g. by improving systems to test and treat them) may help slow the emergence of antimicrobial resistance in E. coli.

Using multivariable models, we compared whether there were significant differences between reported outbreak and sporadic cases in terms of their sex, age, and mode and site of disease transmission. We also determined the potential role of administrative, temporal, and spatial factors within these models. We compared a variety of approaches to account for clustering of cases in outbreaks including weighted logistic regression, random effects models, general estimating equations, robust variance estimates, and the random selection of one case from each outbreak. Age and mode of transmission were the only epidemiologically and statistically significant covariates in our final models using the above approaches. Weighing observations in a logistic regression model by the inverse of their outbreak size appeared to be a relatively robust and valid means for modelling these data. Some analytical techniques, designed to account for clustering, had difficulty converging or producing realistic measures of association.

We obtained a list of all reported cases of Escherichia coli O157 in Alberta during the 2000-2002 period, and using scan statistics we identified yearly temporal and spatial clusters of reported cases of E. coli O157 during the summer and in southern Alberta. However, the location of the spatial cluster in the south was variable among years. The impact of using both outbreak and sporadic data or only sporadic data on the identification of spatial and temporal clusters was small when analysing individual years, but the difference between spatial clusters was pronounced when scanning the entire study period. We also identified space-time clusters that incorporated known outbreaks, and clusters that were suggestive of undetected outbreaks that we attempted to validate with molecular data. Our results suggest that scan statistics, based on a space-time permutation model, may have a role in outbreak investigation and surveillance programmes by identifying previously undetected outbreaks.

A survey to estimate the prevalence of antimicrobial resistance in Escherichia coli was conducted in 7 Canadian federally inspected processing plants during 2001. Escherichia coli isolates were recovered during routine hazard analysis critical control point sampling from beef carcasses and trim and subsequently tested for their antimicrobial susceptibility by using susceptibility panels. Of the 2653 isolates analyzed, 68% were sensitive to all 18 antimicrobials tested. For 14 of the 18 antimicrobials evaluated, the percentage of resistant isolates was < or = 1. Twenty-five percent of the isolates were resistant to tetracycline, 9% to sulfamethoxazole, 7% to streptomycin, and 3% to ampicillin. Multiple resistance was found in 12% of the isolates, with 7% showing resistance to 2 antimicrobials, 2% to 3 antimicrobials, 2% to 4 antimicrobials, and 1% to 5 or more antimicrobials. Forty-five different antimicrobial resistance patterns were observed. The reasons for the development of the antimicrobial resistance were not investigated in this study. This study was useful as a pilot to help to develop a national antimicrobial resistance surveillance program in Canada. This study indicates that laboratory standardization is possible for consistent results across the country and that the indicator organism, E. coli, is fairly easy to obtain for surveillance but Salmonella are not, due to their low prevalence in beef.