In this study, we explored non-disease factors that affect partial carcass condemnations at provincial abattoirs across Ontario. An advantage of this study was that historical data were available during a time when large-scale disease events took place for performance evaluation. We used multivariable statistical models that included a random intercept for repeated observations from abattoirs to explore the relationships between temporal, regional, seasonal and abattoir-related factors for both lung and kidney condemnations. We also evaluated spatial, temporal and space-time clusters of high rates of kidney and lung partial carcass condemnations in reference to the widespread outbreaks of PCVAD, PRRSv and swine influenza virus that took place.
Pneumonia is one of the most frequently seen clinical features of PCVAD, and broncho-interstitial pneumonia was a common pathological feature of PCV-2 cases seen at the AHL during the outbreak [1
]. Nephritis was another pathological feature of the PCVAD outbreak cases [1
], can also be caused by PRRSv infection [25
], and is easily visualized on post-mortem inspection. We expected that these two condemnation categories would be good indicators for the detection of the large-scale outbreaks of PCVAD, PRRS and swine influenza. Lung condemnations due to pneumonia and kidney condemnations due to nephritis were both prevalent causes for partial condemnations of hogs in provincial abattoirs during 2001-2007 (Additional file 1
, Table S1). Results from our negative binomial models and scan statistics revealed that lung condemnation data were not useful for capturing trends in condemnations related to these outbreaks. In contrast, some of the results from our models and scan statistics using the data pertaining to kidney condemnations in eastern Ontario mirrored expected findings during the timeframe when the PCV-2 outbreak occurred. Of note, one space-time cluster of kidney condemnations took place earlier than a cluster of PCV-2 cases detected using traditional lab data [27
]. The space-time permutation model controls for purely spatial clusters, which is important because of the regional differences in lung and kidney condemnations detected by our models. Model-adjusted space-time scan statistics may further improve upon cluster detection [28
]. To determine whether space-time clusters are the result of true disease outbreaks, validation with other information, such as source farm and laboratory records would be required before a formal prospective system is introduced.
Marked differences in condemnation rates for pigs with pneumonia and partial carcass condemnations are found between abattoirs in other countries with well-developed meat inspection, including Belgium [30
], Denmark [31
] and Italy [32
]. A study in Denmark also demonstrated large variability in the sensitivity and specificity of traditional inspection related to chronic pleuritis lesions between 4 abattoirs that was greatly improved by more detailed, standardized post-mortem inspection [32
]. It is possible that our data were affected by variations in the sensitivity and specificity of lesion detection between individual abattoirs and over time. Our space-time scans should have adjusted for purely spatial clusters. Standardized recording, such as described for scoring lung lesions [32
] could also be employed by abattoirs to reduce biases related to variation of lesion recording. This would likely result in some cost to timeliness of data collection and would require enhanced training of meat inspectors.
A feature of provincially-inspected abattoirs in Ontario that differs from abattoirs in a number of other countries is that a lay meat inspector may partially condemn pig carcasses in provincial abattoirs in the absence of direct veterinary oversight [34
]. Provincial meat inspectors undergo a rigorous classroom and field training program, and efforts are underway to improve standardization of inspection procedures across the province [35
]. Standard guidelines are used for classifying pathological lesions for partial and whole carcass condemnations according to the Canadian Food Inspection Agency's Meat Hygiene Manual of Procedures [36
]. However, there may be greater variability in the classification of partial condemnation lesions among non-veterinary inspectors with less specialized training in pathology, anatomy and specific disease conditions, leading to increased recording bias between inspectors and individual abattoirs. Regardless of jurisdictional meat inspection training requirements, the subjective nature of meat inspection makes observational and operator bias a concern, especially when combining data from multiple slaughterplants for spatial and space-time surveillance applications.
An association between larger abattoirs and lower condemnation rates for both lung and kidney condemnations agreed with findings that demonstrated the same effect for whole carcass condemnation rates [14
]. One plausible explanation to explain this finding is that pigs being shipped to larger abattoirs have higher health status. Another reason behind this association might be the effect of faster processing speeds in large abattoirs on the ability of inspectors to thoroughly examine a carcass and/or record lesions. Unfortunately, we did not have access to processing line speeds or source farm information to explore these relationships.
There were no significant seasonal trends in partial condemnation rates related to lung lesions, which is inconsistent with previous research documenting a higher rate of lesions consistent with pneumonia in finisher pigs slaughtered during the winter months in a Federal abattoir [12
]. Research by Tuovenin et al. detected seasonal variation in partial carcass condemnation data when using moving monthly averages [37
] instead of quarterly rates as was used in our study. In terms of secular changes, results from our multi-level models using lung condemnation data predicted a decline across the study period in all regions. In 2001 there was an update made to the Code of Practice for the humane transport of farm animals [38
], enforced by the CFIA and OMAFRA, whereby producers would be reported to the CFIA and penalized by issuance of an Administrative Monetary Penalty (AMP) if any pigs arriving at an abattoir exhibited severe signs of illness would be euthanized after reporting to the CFIA for (personal communication Ab Rehmtulla, DVM, OMAFRA, Stone Road, Guelph, Ontario). Perhaps the institution of monetary penalties lead to a decline in the number of pigs shipped to abattoirs showing signs of severe respiratory disease, compared to other less observable signs of disease that might be detected upon post-mortem inspection.
Higher rates of kidney condemnations in northern Ontario during the winter and fall compared to spring and summer, however, suggest that the incidence of nephritis in this colder area of the province may be influenced more by seasonal climactic variations compared to other regions in the province. We did not find a significant association between region and season for the lung condemnation data, and the predicted trends in lung condemnation rates did not coincide with the expected timeframes during which respiratory diseases were high in any of the agricultural regions in Ontario. Furthermore, there were no documented outbreaks of respiratory disease or diseases that cause nephritis in the province to explain the high rates of nephritis and pneumonia condemnations found in the data during 2001-2004. In contrast, the yearly trends in kidney nephritis condemnation rates that were predicted by the final model in eastern Ontario were consistent with expected increases in nephritis during the PCV-2 outbreak, and the third most likely space-time cluster, which coincided with the most likely spatial cluster for high kidney condemnation rates due to nephritis, took place in eastern Ontario during the timeframe in which the PCV-2 outbreak was known to have occurred. The decline in cases observed at the AHL by the spring of 2006, when the PCV-2 vaccine was introduced into swine herds in Ontario [28
], coincides with the end of the third most likely space-time cluster of nephritis condemnations. Additionally, the decline in predicted rates of kidney condemnations due to nephritis in eastern Ontario from our multilevel models coincides with this cluster. Interestingly, very low rates of kidney condemnations were predicted in southern and western Ontario. There is no documented evidence to suggest lower rates of PCVAD took place in these regions during the outbreak.
Previous research [13
], has demonstrated that regional differences influence condemnation data from provincially-inspected Ontario abattoirs. These differences may reflect different herd and farm densities, disease prevalence, and on farm management factors. It is also possible that plants in different regions may have different processing and inspection practices. Regardless of the reason for the spatial variation, by employing cluster detection methods that control for regional effects, it is possible to avoid these potential biases. For example, lung tissue from pigs is generally not processed for human consumption in provincial abattoirs, and at some abattoirs there may be less stringent recording of lung lesions in comparison with tissues that are important from a food safety and economic perspective. Furthermore, in plants where scalding tanks are used for de-hairing the pig carcass, lung tissue can become contaminated with scalding tank water and lung pathology can not consistently be evaluated (personal communication, Dr. Georges Branov, OMAFRA). Thus, clusters of high lung condemnation rates in space may represent different plant processing characteristics and/or reporting tendencies. The small spatial cluster of non-reporting of lung condemnations in southern Ontario may be related to the processing method (i.e. scalding tanks) used in abattoirs in this region, but we did not have information pertaining to individual abattoir de-hairing processes to further explore this as an underlying cause. Studies that investigate individual abattoir processing methods and their relation to condemnation information would be useful to improve our understanding of the extent that different methods bias condemnation data for disease surveillance.
To account for concerns regarding biasing factors that may be underlying the spatial clusters of high rates of kidney and lung condemnations, the space-time permutation model adjusts for purely spatial and temporal clusters that might exist in the data [39
]. The third most likely space-time cluster of high kidney condemnation rates due to nephritis was detected during a time when the PCV-2 outbreak occurred in Ontario, and preceded temporal clusters of PCV-2 positive cases detected at the Animal Health Laboratory [27
]. There were no significant spatio-temporal clusters of high rates of pneumonia found to predate or coincide with the timeframe during which there was widespread respiratory disease in finisher pigs in the province [1
]. Temporal clusters of both kidney and lung condemnation categories did not correspond with the 2004-2006 outbreaks of PCV-2, swine influenza and PRRS. Since these temporal scans use data from all regions simultaneously, they are less sensitive at detecting a temporal change in a localized area.
Previous research that examined data collected from federally-inspected abattoirs supported the use of lung and kidney condemnation data for disease surveillance [12
]. Because kidneys and lungs may be exported to countries that utilize these offal for pork products, this market difference, in addition to the requirement for licensed veterinary inspectors to oversee partial carcass condemnations in federally-inspected abattoirs, may result in improved data quality. However, federally-inspected abattoirs are large and there are only five that receive pigs from across the province of Ontario [12
]. In contrast, provincially-inspected abattoirs are numerous and tend to be supplied by more local farms [13
] making them more suited to the use of spatial and space-time surveillance methods. As a consequence of international trade restrictions, federal abattoirs in Canada may handle pigs that are, on average, of higher health status in comparison with provincial abattoirs, making provincial abattoirs more likely to detect disease outbreaks. Rates of condemnations related to pneumonia and nephritis were indeed higher than those found in an investigation of one Canadian federally-inspected abattoir [12
], though the rates of pneumonia and nephritis in Ontario provincial abattoirs were lower on average than found in previously reported studies from other countries [30
]. Without international standards for procedures and condemnation judgements at abattoirs, it is difficult to compare our results with those from other countries. While findings from our study are applicable to countries with well-developed meat inspection processes, they may be of particular interest for jurisdictions with numerous small abattoirs supplied by local farms [41
While a number of statistical methods have been proposed and implemented in syndromic surveillance systems [42
], each has advantages and limitations, and there is no clear consensus as to which are the most timely, sensitive and specific methods for analyses of various syndromic data [43
]. An advantage of using the space-time scan statistic for cluster detection is that this method does not require the specification of baseline risk levels. However, in a prospective system, the specification of a reference time period is required, which may impact the sensitivity and specificity of cluster detection. The space-time permutation model is susceptible to population shift bias, whereby shifts in the background population distribution may create an interaction in space and time that is not related to increased disease risk [43
]. The magnitude of this bias is generally a greater issue when investigating clusters in longer study periods, or numerous production cycles. In our study the 7-year timeframe during which some abattoirs closed across Ontario may have allowed population shift dynamics to bias the clusters that were detected. By shortening the length of time for our temporal and space-time scans and running multiple scans to cover the study period, the potential for population shift bias to impact results may be reduced. Another limitation of the scan statistic as it was applied in this study included the requirement to use circular scanning windows. Employing a scan statistic using flexibly shaped scanning windows may improve delineation of irregularly shaped clusters, such as those in irregularly shaped geographic locations [44
] like the areas in Ontario that are bounded by the Great Lakes. However, for early outbreak detection, timeliness is most important and the circular-based scan performed better at cluster detection compared to a flexible scanning window during the early stages of an outbreak [44
]. Applying scan statistics after adjusting for the effects of non-disease factors based on statistical models may improve upon cluster detection of true disease events [28
]. Even sentinel-based surveillance systems should consider biases that could be corrected using these techniques.
Diseases in pigs such as PCV-2 and PRRS are often associated with co-infections involving a number of agents [1
], pathogenesis is often multi-systemic [45
], and pathological conditions such as nephritis can be caused by other primary agents, such as Leptospirosis [48
] or porcine parvovirus (PPV) [26
]. Specificity of gross pathological data are likely reduced when multiple etiologic agents can contribute to condemnations within the same syndrome category. However, the focus of a syndromic surveillance system is to detect changes in syndromes rather than a specific disease. Early warning based on less specific pre-diagnostic data are followed by more specific laboratory testing to determine the etiologic agents involved.
For any prospective disease surveillance system that uses data from slaughter plants, it is important to have traceability systems in place for rapid validation of clusters of high condemnation rates with farm-level and laboratory information. Canada is currently developing a system that will allow for the identification of all pig movements from farm to abattoir in the event of disease outbreaks [49
]. In addition to traceability issues, there are other barriers to implementation of a syndromic surveillance system for pigs in Ontario at the present time. These include data privacy concerns, the need to integrate the data with existing disease surveillance systems, and practical issues pertaining to the collection, specialized training and personnel available for data collection. Any purposeful, standardized collection of data would need to be seamlessly integrated into procedures already in place at the abattoir. Development of timely validation and response procedures in the event of cluster detection is also required.
A prospective system that incorporates the purposeful, standardized collection of partial condemnation data pertaining to organs of interest for disease surveillance could be validated with other health information. The validity, sensitivity and specificity of these data for disease outbreak detection could thus be evaluated. An investigation is presently underway to assess whether whole carcass condemnations related to conditions including systemic sepsis, arthritis, and emaciation may be more appropriate for disease surveillance in this population of pigs.