This paper presents a historical review of antimicrobial use in food animals, the causes of residues in meat and milk, the types of residues found, their regulation in Canada, tests used for their detection, and test performance parameters, with an emphasis on immunoassay techniques. The development of residue detection methods began shortly after the introduction of antimicrobials to food animal production in the late 1940s. From initial technical concerns expressed by the dairy industry to the present public health and international trade implications, there has been an ongoing need for reliable, sensitive, and economical methods for the detection of antimicrobial residues in food animal products such as milk and meat. Initially there were microbial growth inhibition tests, followed by more sensitive and specific methods based on receptor binding, immunochemical, and chromatographic principle. An understanding of basic test performance parameters and their implications is essential when choosing an analytical strategy for residue testing. While each test format has its own attributes, none test will meet all the required analytical needs. Therefore the use of a tiered or integrated system employing assays designated for screening and confirmation is necessary to ensure that foods containing violative residues are not introduced into the food chain.

To estimate the magnitude and distribution of self-reported, acute gastrointestinal illness in a Canadian-based population, we conducted a retrospective, cross-sectional telephone survey of approximately 3500 randomly selected residents of the city of Hamilton (Ontario, Canada) from February 2001 to February 2002. The observed monthly prevalence was 10% (95 % CI 9.94-10.14) and the incidence rate was 1.3 (95 % CI 1.1-1.4) episodes per person-year; this is within the range of estimates from other developed countries. The prevalence was higher in females and in those aged < 10 years and 20-24 years. Overall, prevalence peaked in April and October, but a different temporal distribution was observed for those aged < 10 years. Although these data were derived from one community, they demonstrate that the epidemiology of acute gastrointestinal illness in a Canadian-based population is similar to that reported for other developed countries.

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Raw (unpasteurized) milk can be a source of food-borne pathogens. Raw milk consumption results in sporadic disease outbreaks. Pasteurization is designed to destroy all bacterial pathogens common to raw milk, excluding spore-forming bacteria and possibly Mycobacterium paratuberculosis, but some people continue to drink raw milk, believing it to be safe. Current methods for assessing the bacteriological quality of raw milk, such as aerobic plate counts, are not usually designed to detect specific pathogens. The objective of this study was to estimate the proportion of pick-ups (loads of raw milk from a single farm bulk tank) from Ontario farm bulk tanks that contained Listeria monocytogenes. Salmonella spp., Campylobacter spp., and/or verotoxigenic Escherichia coli (VTEC). Samples from 1,720 pick-ups of raw milk were tested for the presence of these pathogens, and 47 L. monocytogenes, three Salmonella spp., eight Campylobacter spp., and 15 VTEC isolates were detected, representing 2.73, 0.17, 0.47, and 0.87% of milk samples, respectively. Estimates of the proportion of theoretical tanker truck loads of pooled raw milk contaminated with pathogens ranged from a low of 0.51 % of tankers containing raw milk from 3 bulk tanks being contaminated with Salmonella spp. to a high of 34.41 % of tankers containing raw milk from 10 bulk tanks being contaminated with at least one of the pathogens. Associations between the presence of pathogens and raw milk sample characteristics were investigated. The mean somatic cell count was higher among VTEC- or L. monocytogenes-positive samples, and the mean aerobic plate count was found to be higher among L. monocytogenes-positive samples. These results confirm the presence of bacterial food pathogens in raw milk and emphasize the importance of continued diligence in the application of hygiene programs within dairies and the separation of raw milk from pasteurized milk and milk products.

BackgroundOntario provincial abattoirs have the potential to be important sources of syndromic surveillance data for emerging diseases of concern to animal health, public health and food safety. The objectives of this study were to: (1) describe provincially inspected abattoirs processing cattle in Ontario in terms of the number of abattoirs, the number of weeks abattoirs process cattle, geographical distribution, types of whole carcass condemnations reported, and the distance animals are shipped for slaughter; and (2) identify various seasonal, secular, disease and non-disease factors that might bias the results of quantitative methods, such as cluster detection methods, used for food animal syndromic surveillance.ResultsData were collected from the Ontario Ministry of Agriculture, Food and Rural Affairs and the Ontario Cattlemen's Association regarding whole carcass condemnation rates for cattle animal classes, abattoir compliance ratings, and the monthly sales-yard price for various cattle classes from 2001-2007. To analyze the association between condemnation rates and potential explanatory variables including abattoir characteristics, season, year and commodity price, as well as animal class, negative binomial regression models were fit using generalized estimating equations (GEE) to account for autocorrelation among observations from the same abattoir. Results of the fitted model found animal class, year, season, price, and audit rating are associated with condemnation rates in Ontario abattoirs. In addition, a subset of data was used to estimate the average distance cattle are shipped to Ontario provincial abattoirs. The median distance from the farm to the abattoir was approximately 82 km, and 75% of cattle were shipped less than 100 km.ConclusionsThe results suggest that secular and seasonal trends, as well as some non-disease factors will need to be corrected for when applying quantitative methods for syndromic surveillance involving these data. This study also demonstrated that animals shipped to Ontario provincial abattoirs come from relatively local farms, which is important when considering the use of spatial surveillance methods for these data.

Understanding contact networks are important for modelling and managing the spread and control of communicable diseases in populations. This study characterizes the swine shipment network of a multi-site production system in southwestern Ontario, Canada. Data were extracted from a company's database listing swine shipments among 251 swine farms, including 20 sow, 69 nursery and 162 finishing farms, for the 2-year period of 2006 to 2007. Several network metrics were generated. The number of shipments per week between pairs of farms ranged from 1 to 6. The medians (and ranges) of out-degree were: sow 6 (1-21), nursery 8 (0-25), and finishing 0 (0-4), over the entire 2-year study period. Corresponding estimates for in-degree of nursery and finishing farms were 3 (0-9) and 3 (0-12) respectively. Outgoing and incoming infection chains (OIC and IIC), were also measured. The medians (ranges) of the monthly OIC and IIC were 0 (0-8) and 0 (0-6), respectively, with very similar measures observed for 2-week intervals. Nursery farms exhibited high measures of centrality. This indicates that they pose greater risks of disease spread in the network. Therefore, they should be given a high priority for disease prevention and control measures affecting all age groups alike. The network demonstrated scale-free and small-world topologies as observed in other livestock shipment studies. This heterogeneity in contacts among farm types and network topologies should be incorporated in simulation models to improve their validity. In conclusion, this study provided useful epidemiological information and parameters for the control and modelling of disease spread among swine farms, for the first time from Ontario, Canada.

Background: In Ontario, infectious gastrointestinal illness (IGI) reporting can be represented by a linear model of several sequential steps required for a case to be captured in the provincial reportable disease surveillance system. Since reportable enteric data are known to represent only a small fraction of the total IGI in the community, the objective of this study was to estimate the under-reporting rate for IGI in Ontario.Methods: A distribution of plausible values for the under-reporting rate was estimated by specifying input distributions for the proportions reported at each step in the reporting chain, and multiplying these distributions together using simulation methods. Input distributions (type of distribution and parameters) for the proportion of cases reported at each step of the reporting chain were determined using data from the Public Health Agency of Canada's National Studies on Acute Gastrointestinal Illness (NSAGI) initiative. Results:For each case of enteric illness reported to the province of Ontario, the estimated number of cases of IGI in the community ranged from 105 to 1,389, with a median of 285, and a mean and standard deviation of 313 and 128, respectively.Conclusions: Each case of enteric illness reported to the province of Ontario represents an estimated several hundred cases of IGI in the community. Thus, reportable disease data should be used with caution when estimating the burden of such illness. Program planners and public health personnel may want to consider this fact when developing populationbased interventions.MeSH terms: Gastroenteritis; infectious disease reporting; surveillance; Ontario; Canada La traduction du résumé se trouve à la fin de l'article.

This study estimated the health burden and costs associated with gastroenteritis in the City of Hamilton (Ontario, Canada). The number of cases, number of different resource units used, and cost per resource unit were represented by probability distributions and point estimates. These were subsequently integrated in a stochastic model to estimate the overall burden and cost in the population and to depict the uncertainty of the estimates. The estimated mean annual cost per capita was Can dollar 115. The estimated mean annual cost per case was Can dollar 1,089 and was similar to other published figures. Gastroenteritis represented a significant burden in the study population, with costs high enough to justify prevention efforts. These results, currently the most accurate available estimates for a Canadian population, can inform future economic evaluations to determine the most cost effective measures for reducing the burden and cost of gastroenteritis in the community.