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Antimicrobial resistance (AMR) is a major public health threat worldwide. The main objective of this study was to compare AMR in Campylobacter from broiler chickens raised on Canadian farms and their products in different geographical regions of Canada. To do this, antimicrobial susceptibility results from isolates of Campylobacter recovered from a national microbiological baseline study conducted in federally registered establishments and in the retail marketplace were analyzed. Among 1460 isolates tested, 774 (53%) were resistant to at least one antimicrobial, with a predominance of three profiles: tetracycline (39%), quinolone–tetracycline (6.6%), and quinolones only (3.5%). The results showed no significant difference in the frequency of resistant profiles (p ≥ 0.05) among the isolates originating from different points in the food processing chain at slaughterhouses and in retail establishments. This suggests that AMR observed in Campylobacter isolates from raw chicken at retail originated further upstream in the system. A difference in the frequency of certain resistance profiles was observed between the regions of Canada. For instance, in British Columbia, there was more resistance to quinolones, while in Ontario and Quebec, Campylobacter isolates were more resistant to tetracyclines, macrolides, ketolides, and lincosamides. Comparison of AMR data from this study with those from the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) did not show any significant difference and provides evidence that CIPARS produces nationally representative resistance results.

The study used a structured expert elicitation survey to derive estimates of food-specific attribution for nine illnesses caused by enteric pathogens in Canada. It was based on a similar survey conducted in the United States and focused on Campylobacter spp., Escherichia coli O157:H7, Listeria monocytogenes, nontyphoidal Salmonella enterica, Shigella spp., Vibrio spp., Yersinia enterocolitica, Cryptosporidium parvum, and Norwalk-like virus. A snowball approach was used to identify food safety experts within Canada. Survey respondents provided background information as well as self-assessments of their expertise for each pathogen and the 12 food categories. Depending on the pathogen, food source attribution estimates were based on responses from between 10 and 35 experts. For each pathogen, experts divided their estimates of total foodborne illness across 12 food categories and they provided a best estimate for each category as well as 5th and 95th percentile limits for foods considered to be vehicles. Their responses were treated as triangular probability distributions, and linear aggregation was used to combine the opinions of each group of experts for each pathogen-food source group. Across the 108 pathogen-food groups, a majority of experts agreed on 30 sources and 48 nonsources for illness. The number of food groups considered to be pathogen sources by a majority of experts varied by pathogen from a low of one food source for Vibrio spp. (seafood) and C. parvum (produce) to a high of seven food sources for Salmonella spp. Beta distributions were fitted to the aggregated opinions and were reasonable representations for most of the pathogen-food group attributions. These results will be used to quantitatively assess the burden of foodborne illness in Canada as well as to analyze the uncertainty in our estimates.

The study used a structured expert elicitation survey to derive estimates of the foodborne attributable proportion for nine illnesses caused by enteric pathogens in Canada. It was based on a similar study conducted in the United States and focused on Campylobacter, Escherichia coli O157:H7, Listeria monocytogenes, nontyphoidal Salmonella enterica, Shigella spp., Vibrio spp., Yersinia enterocolitica, Cryptosporidium parvum, and Norwalk-like virus. For each pathogen, experts were asked to provide their best estimate and low and high limits for the proportion of foodborne illness relative to total cases. In addition, they provided background information with regard to food safety experience, including self-evaluated expertise for each pathogen on a 5-point scale. A snowball approach was used to identify 152 experts within Canada. The experts' background details were summarized using descriptive statistics. Factor analysis was used to determine whether the variability in best estimates was related to self-assessed level of expertise or other background information. Cluster analysis followed by beta function fitting was undertaken on best estimates from experts who self-evaluated their expertise 3 or higher. In parallel, Monte Carlo resampling was run using triangular distributions based on each expert's best estimate and its limits. Sixty-six experts encompassing various academic backgrounds, fields of expertise, and experiences relevant to food safety provided usable data. Considerable variation between experts in their estimated foodborne attributable proportions was observed over all diseases, without any relationship to the expert's background. Uncertainty about their estimate (measured by the low and high limits) varied between experts and between pathogens as well. Both cluster analysis and Monte Carlo resampling clearly indicated disagreement between experts for Campylobacter, E. coli O157, L. monocytogenes, Salmonella, Vibrio, and Y. enterocolitica. In the absence of more reliable estimates, the observed discrepancy between experts must be explored and understood before one can judge which opinion is the best.

This study used integrated surveillance data to assess the seasonality in retail chicken contamination and of human activities and their role on the seasonality of human endemic salmonellosis. From June 2005 to May 2008, reported cases of salmonellosis were followed-up comprehensively using a standardized questionnaire, and 616 retail chicken breasts were systematically tested for Salmonella, in one Canadian community. Poisson regression was used to model seasonality of human cases, Salmonella in retail chicken, and to assess the relationship between these and selected meteorological variables. The case-case approach was used to compare the activities of salmonellosis cases that occurred during the summer peak to the other cases. There were 216 human endemic salmonellosis cases (incidence rate: 14.7 cases/100,000 person-years), predominantly of Typhimurium and Enteritidis serotypes (28.4% and 20.8%, respectively). The monthly distribution of cases was associated with ambient temperature (p0.001) with a significant seasonal peak in June (p = 0.03) and July (p = 0.0005), but it was not associated with precipitation (p = 0.38). Several activities reported by cases tended to be more frequent during summer. Particularly, attending a barbeque and gardening within the 3 days before the disease onset were two significant risk factors for salmonellosis in June or July compared with the salmonellosis cases that occurred in the other months. Out of all chicken samples, 185 (30%) tested positive for Salmonella spp., Kentucky being the dominant serotype (44.3% of positive samples). The monthly proportion of positive chicken samples showed no seasonal variations (p = 0.30) and was not associated with the monthly count of human cases (p = 0.99). In conclusion, even though evidence generally supports chicken as a primary vehicle of Salmonella to humans, the contamination of retail chicken was not driving the seasonality in human salmonellosis. Attending a barbeque or gardening during the hotter months of the year should be further assessed for their risk.