Animal disease outbreaks can have a devastating effect, not only on animals, but to the food-animal industry, public, economy, and international trade [1–3]; therefore, research and development of novel animal disease surveillance systems is extremely important. In recent years, Ontario has experienced the emergence of various infectious animal diseases including a new strain of porcine circovirus type II (PCV-2) in 2004[4], outbreaks of bovine viral diarrhea (BVD) with enhanced virulence in cattle in the early 90’s [3], and the impact of the identification of a small number of cases of bovine spongiform encephalopathy (BSE) in Alberta, Canada in 2003[2]. The confirmation of BSE in May 2003 is just one of many examples of how the emergence of an infectious animal disease can cripple an industry and have profound lasting effects [2]. Though all BSE cases in Canada were only identified in Alberta, Canada, closure of international trade borders to Canadian cattle caused the price of cattle to drop significantly throughout the country and took several years to recover [5]. New approaches to animal disease surveillance, such as syndromic surveillance of condemnation data may be important for the timely identification of infectious animal and zoonotic disease events in the future.

Syndromic surveillance, though an increasingly popular tool in public health surveillance research [6–9] has only recently been explored as an option for animal health surveillance. One novel way to target surveillance of infectious animal and zoonotic diseases would be through the food system. In the past, abattoirs have been the focus for surveillance at this human-animal interface, usually involving targeted surveillance of a specific disease [10–13]. In recent years, research has been expanded to include surveillance of food animal data from a variety of sources including on-farm surveillance [14, 15], sales-yard surveillance [16], as well as syndromic surveillance using abattoir condemnation data [17–19].

Abattoir condemnation data have the potential to provide early warning of emerging animal and zoonotic diseases, particularly provincial abattoir data and yet these data have been under-utilized in the past. Portion condemnations and whole carcass condemnation data have been previously described in the literature [20–22], however, few reports of potential usages of these data for syndromic surveillance purposes have been implemented. Changes in portion and whole carcass condemnation rates could be monitored over time and space, and when the condemnation rate reaches a certain threshold it may signal a potential outbreak or quality control problem within an abattoir and/or region. In Ontario, condemnation data from provincially inspected abattoirs are particularly useful for syndromic surveillance, as they give a relatively local perspective on the health of animals within the province. Ontario provincial abattoirs only distribute their products within the province, compared to federal abattoirs, which ship their products inter-provincially and internationally [23]. Anecdotal evidence has suggested that cattle shipped to Ontario provincial abattoirs originate from relatively local farms. This was confirmed by a previous study which found that 75% of cattle from Ontario provincial abattoirs originated from farms less than 94 kilometres from the abattoir [17]. Previous research has investigated the use of whole carcass condemnation data for syndromic surveillance [17]. It is unclear whether organ/body system data may be better suited for syndromic surveillance, as these data may provide more specific information on health outcomes than whole carcass condemnation data. By having a more specific outcome, it is hypothesized that portion condemnation data should be more sensitive than whole carcass data because inspectors condemn a carcass for one reason. However, bovine carcasses may have several disease conditions causing the condemnation of the carcass; whereas organs are less likely to have more than one reason for condemnation and reflect diseases found in a specific organ system.

Generalized linear mixed models (GLM) have been previously used for human disease surveillance [24], as well as clustered GLM’s fit by generalized estimating equations (GEE) specifically for whole carcass condemnation data [17]. Various seasonal, secular, disease, and non-disease factors were previously found to have a statistically significant association with bovine whole carcass condemnation rates, and should be controlled for in the application of quantitative surveillance methods to prevent biased results (e.g. false alarms) [17]. It was unclear whether the same factors would also be significantly associated with condemnation data when applied to portion condemnation data.

The objective of this study was to identify various seasonal, secular, and abattoir characteristic factors that may be associated with bovine portion condemnation rates and compare how these may differ from factors associated with bovine whole carcass condemnation rates. “Parasitic liver” and pneumonic lung condemnations were used in this case study as these condemnation classes were a rich source of data.

Portion and whole carcass condemnation data may have an important role in the development of a food animal syndromic surveillance system. These data provide insight into lesions on carcasses and organs, which may lead to early detection of emerging animal and zoonotic diseases. This study builds upon previous research investigating biological and non-biological factors associated with bovine whole carcass condemnation rates in Ontario provincial abattoirs during the same study period [17]. As with whole carcass data, various seasonal, secular and abattoir characteristic factors were found to have an association with liver and lung portion condemnations, and need to be taken into account in the application of quantitative methods, such as cluster detection for disease surveillance involving these data. In addition, the results show differences in the models constructed for liver and lung portion condemnations, as well as between portion and previously explored whole carcass condemnation data [17]. These findings suggest that different variables may be associated with condemnation rates depending on the type of material being condemned, and should be modeled and controlled for during quantitative surveillance on a portion-specific basis. Previous studies have demonstrated the importance of identification of potential confounding variables and different methods of controlling for these variables in cluster detection methods for disease surveillance [26, 27]. For example, a study by Kleinman et al. [26] compared the performance of the space-time scan statistic using unadjusted and covariate-adjusted respiratory complaint data in humans to account for confounding temporal factors such as day of the week, month and holidays. The study concluded that failure to adjust for confounding variables can produce many false alarms and/or mask potential outbreaks.

Pneumonic lungs and “parasitic” livers were used as examples to explore the modeling of biological and non-biological factors associated with portion condemnations. These condemnation designations were selected as they represented two of the most frequently reported reasons for portion condemnations by inspectors at provincial abattoirs during the study period. Syndromic surveillance is based on non-traditional data sources. Though this allows for early warning about potential disease outbreaks these systems are generally less sensitive than traditional laboratory based surveillance systems [28]. Therefore it is of utmost importance to (i) use highly predictive models (adjusted for known risk factors and confounders), and (ii) preserve the robustness of the models by adhering to the principle of parsimony. These are well known contradicting goals in predictive modeling that make sufficient/large sample sizes an important requirement. Therefore, pneumonic lung and “parasitic liver” condemnation rates were selected as they were a rich data source from which to estimate trends. Livers are important from a public health and economic standpoint, as they are a common edible portion in cattle and represent a possible food safety concern. Lungs, though generally not consumed by the average Ontarion, are also an important animal and public health concern, as lesions such as tuberculosis granulomas may be found in inedible organs/tissues such as the lungs. These are important factors to consider when selecting portion condemnation designations for syndromic surveillance; a previous study by Thomas et al. [19], investigating the use of portion condemnations in market hogs, noted that the quality of data recording was poor for organs that were not considered to be economically important or a concern for food safety.

It was interesting to find similarities and differences in terms of the significant variables and the impact the variables had on condemnation rates in both the liver and lung portion models, as well as the previously described models for whole carcass condemnations [17]. The variables year, animal class, season and annual audit rating were found to be significantly associated with condemnation rates in both portion models as well as whole carcasses. It is not surprising that season and animal class were found to be significant factors associated with abattoir condemnation rates in all three models, as many animal diseases tend to have a distinct seasonality and high risk age groups associated with the disease. For example, bovine respiratory disease complex more commonly infects calves following a stressful event, such as sudden change in weather conditions [29], and older cattle are generally at higher risk for being culled due to disease and thus condemned more frequently. In the whole carcass condemnation data, the variable year, identified patterns assumed to be associated with the discovery of Bovine Spongiform Encephalopathy (BSE) in Alberta, Canada in 2003 [17]. In the portion models, year also appeared to have a significant decreasing trend in calves for pneumonic lung condemnations. It is suspected that these temporal trends in liver and lung condemnations also stem from regulation changes due to BSE. Prior to BSE in Canada, it was legal to load and transport downer animals with a veterinary certification of fitness for slaughter. However, during 2004, changes were made to federal cattle transportation regulations which forbid the transportation and slaughter of non-ambulatory animals [30]. Ambulatory animals may be less likely to have lung pathology than compromised and downer animals and are likely reflected in the marked decrease in condemnation rates in pneumonic lungs (personal communication Ab Rehmtulla, DVM, OMAFRA, Stone Road, Guelph, Ontario). In contrast, “parasitic liver” condemnations increased in cows over the study period and may also reflect the type and quality of cattle being sent to slaughter; however, it is unclear why an increase was seen over the study period. Audit rating appeared to be an important variable for provincial abattoir condemnation data. It was hypothesized that audit rating may reflect an abattoir’s compliance to regulations and/or willingness to accept animals of poorer quality. Although, different trends were found in these variables between all 3 models, the overall statistically significant association of these variables with condemnation rates appears to be “universal” within Ontario provincial abattoir data, and should be controlled for in quantitative cluster detection methods for surveillance. Although the AAA and C categories represent a small number of abattoirs over the study period, we felt that it was important to not collapse the categories, as these abattoirs point to unique qualities among these establishments. Since this study was conducted, the audit rating system was simplified in September 2010 to a 3-grade system including pass, conditional pass and fail to better reflect systems used in several jurisdictions for evaluating food safety at restaurants [25]. This change in reporting may need to be accounted for in future studies and/or in attempts to control for non-disease issues when conducting space-time cluster analyses.

Agricultural region was found to be significantly associated with the portion condemnation rates but not with whole carcass rates. It was interesting to note that overall, predicted condemnation rates for bovine lungs and liver were lower in northern and southern Ontario regions compared to other regions for all animal classes throughout the study period. This pattern was particularly evident in the lung dataset. This regional difference of condemnation rates in pneumonic lungs may reflect a genuine regional difference; however, it likely stems from the quality of animals being sent to slaughter in these regions. Abattoirs in southern and northern Ontario did not specialize and rarely received non-ambulatory cattle. Prior to 2004, most of the so-called “downer plants” were located in southwestern, central and eastern Ontario. While the regional differences in “parasitic” livers may be due to a smaller concentration of dairy cattle in northern and to some extent southern Ontario, corresponding with the lower condemnation rates in these areas; it was surprising that variables related to abattoir processing capacity, such as number of cattle processed each year and number of weeks an abattoir processed cattle was only significant in the lung condemnation model. This may reflect issues with processing speeds within abattoirs, perhaps the speeds impact lung inspection more than livers since livers are more commonly considered to be an edible portion of cattle and thus more carefully inspected.

It is important to identify and understand the factors which may cause “noise” in the data before any quantitative methods can be chosen for disease surveillance. This extra work beforehand can save valuable time and resources investigating “false alarms” after the application of quantitative methods. Although differing results were found in the two portion models as well as the previously described whole carcass model, common themes arose from the results. Bovine abattoir condemnation data are sensitive to the effects of regulatory and economic changes in the industry. Therefore it is important to adjust models as regulations change over time. In addition, seasonal, secular, and non- disease factors, such as commodity class, abattoir rating and processing capacity also seemed to be important factors for bovine abattoir condemnation data and should be adjusted in subsequent cluster detection analyses to prevent biased results. All analyses thus far have been conducted retrospectively, facilitating the use of historical data to highlight variables which need to be taken into account prior to applying outbreak detection methods. However, the practical application of disease surveillance would be conducted prospectively, and would have implications on the models. For example, the variable year was found to be a very important variable in all of the models; however this variable would not be applicable in a prospective analysis. The secular trend effect would have to be accounted for in the analyses in some other way, for example using a trend polynomial or trend filter. In addition, we were only able to account for clustering by abattoir. However, it would be useful to explore the effect of clustering by inspector as well. Unfortunately, these data were not available to explore the effect of inspector. Specific training of inspectors may also improve the ability of a syndromic surveillance system to detect unusual events. For example, the broad use of the category “parasitic liver” may be more useful at detecting changes in disease if inspectors used more specific criteria when condemning organs.

The suitability of portion vs. whole carcass condemnation data for syndromic surveillance is difficult to ascertain in this study. It is suspected that for syndromic surveillance purposes, portion condemnation data will be more specific and sensitive at detecting changes in condemnation rates. However, validation of this conclusion is difficult with no major documented disease outbreaks in Ontario cattle during the study period. Nevertheless, it is encouraging that regulatory changes surrounding the identification of BSE in Alberta, Canada was identified in both the whole carcass and portion condemnation data. A similar study in pigs using Ontario provincial abattoir data found that whole hog carcass condemnation data performed better than portion carcass condemnation data at detecting disease clusters consistent with a documented porcine circovirus-associated disease outbreak in Ontario [19]. Further investigations, perhaps using simulated data, are needed to determine which types of data are more suitable for the syndromic surveillance of specific types of diseases.

Findings from this study suggest that there are “universal” factors associated with condemnation data, such as animal class, year, season and audit rating, additional material-specific covariates are important and should be modeled and controlled for in quantitative methods for disease surveillance, such as in cluster detection methods. Validation of results is an issue with bovine portion abattoir condemnation data, as there were no documented outbreaks in Ontario cattle during the study period. Further investigations are needed to determine whether portion data would perform better than whole carcass condemnation data for disease surveillance, and whether certain portions are more appropriate than whole carcass for the surveillance of specific diseases.