Assessment of autoregressive integrated moving average (ARIMA), generalized linear autoregressive moving average (GLARMA), and random forest (RF) time series regression models for predicting influenza A virus frequency in swine in Ontario, Canada.

Influenza A virus commonly circulating in swine (IAV-S) is characterized by large genetic and antigenic diversity and, thus, improvements in different aspects of IAV-S surveillance are needed to achieve desirable goals of surveillance such as to establish the capacity to forecast with the greatest accuracy the number of influenza cases likely to arise. Advancements in modeling approaches provide the opportunity to use different models for surveillance. However, in order to make improvements in surveillance, it is necessary to assess the predictive ability of such models. This study compares the sensitivity and predictive accuracy of the autoregressive integrated moving average (ARIMA) model, the generalized linear autoregressive moving average (GLARMA) model, and the random forest (RF) model with respect to the frequency of influenza A virus (IAV) in Ontario swine. Diagnostic data on IAV submissions in Ontario swine between 2007 and 2015 were obtained from the Animal Health Laboratory (University of Guelph, Guelph, ON, Canada). Each modeling approach was examined for predictive accuracy, evaluated by the root mean square error, the normalized root mean square error, and the model's ability to anticipate increases and decreases in disease frequency. Likewise, we verified the magnitude of improvement offered by the ARIMA, GLARMA and RF models over a seasonal-naïve method. Using the diagnostic submissions, the occurrence of seasonality and the long-term trend in IAV infections were also investigated. The RF model had the smallest root mean square error in the prospective analysis and tended to predict increases in the number of diagnostic submissions and positive virological submissions at weekly and monthly intervals with a higher degree of sensitivity than the ARIMA and GLARMA models. The number of weekly positive virological submissions is significantly higher in the fall calendar season compared to the summer calendar season. Positive counts at weekly and monthly intervals demonstrated a significant increasing trend. Overall, this study shows that the RF model offers enhanced prediction ability over the ARIMA and GLARMA time series models for predicting the frequency of IAV infections in diagnostic submissions.

Eternally Vulnerable: The Pathology of Abuse in Domestic Animals.

Animals are amongst the most vulnerable of all sentient beings. Animal neglect and abuse may involve a single animal and one person, or hundreds of animals and many people. Animals and people are victims of the same types of fatal injury and severe neglect; however, the anatomy and physiology of different animal species and even breeds of animals are a unique challenge for veterinary pathologists. Identifying and describing external lesions of blunt force trauma and projectile wounds requires that the entire skin be reflected from the animal because fur and feathers partially or totally mask the injuries. Because quadrupeds or birds may react differently to the same traumatic force applied to bipedal humans, extrapolating from medical forensic pathology must be done with caution. Animal abuse, however, does not occur in a vacuum. An established link exists between animal abuse, interpersonal violence, and other serious crimes. Using examples, this paper describes specific injuries in abused and neglected animals in the context of domestic violence, interpersonal violence, mental illness, and drug addiction. Medical examiners should be aware that animal abuse affects not only the animal, but individuals, families, and society as a whole.

Red Fox as Sentinel for Blastomyces dermatitidis, Ontario, Canada.

Blastomyces dermatitidis, a fungus that can cause fatal infection in humans and other mammals, is not readily recoverable from soil, its environmental reservoir. Because of the red fox's widespread distribution, susceptibility to B. dermatitidis, close association with soil, and well-defined home ranges, this animal has potential utility as a sentinel for this fungus.

Surveillance of antimicrobial resistance in clinical isolates of Pasteurella multocida and Streptococcus suis from Ontario swine.

Susceptibility results for Pasteurella multocida and Streptococcus suis isolated from swine clinical samples were obtained from January 1998 to October 2010 from the Animal Health Laboratory at the University of Guelph, Guelph, Ontario, and used to describe variation in antimicrobial resistance (AMR) to 4 drugs of importance in the Ontario swine industry: ampicillin, tetracycline, tiamulin, and trimethoprim-sulfamethoxazole. Four temporal data-analysis options were used: visualization of trends in 12-month rolling averages, logistic-regression modeling, temporal-scan statistics, and a scan with the "What's strange about recent events?" (WSARE) algorithm. The AMR trends varied among the antimicrobial drugs for a single pathogen and between pathogens for a single antimicrobial, suggesting that pathogen-specific AMR surveillance may be preferable to indicator data. The 4 methods provided complementary and, at times, redundant results. The most appropriate combination of analysis methods for surveillance using these data included temporal-scan statistics with a visualization method (rolling-average or predicted-probability plots following logistic-regression models). The WSARE algorithm provided interesting results for quality control and has the potential to detect new resistance patterns; however, missing data created problems for displaying the results in a way that would be meaningful to all surveillance stakeholders.

Les résultats de sensibilité pour des isolats de Pasteurella multocida et Streptococcus suis provenant d'échantillons cliniques de porcs furent obtenus du Animal Health Laboratory de l'Université de Guelph pour la période de janvier 1998 à octobre 2010, et utilisés pour décrire la variation dans la résistance antimicrobienne (AMR) à quatre antibiotiques d'importance dans l'industrie porcine en Ontario : l'ampicilline, la tétracycline, la tiamuline, et le trimethoprime-sulfaméthoxazole. Quatre options temporelles d'analyse des données ont été utilisées : visualisation des tendances des moyennes mobiles de 12 mois, modélisation de régression logistique, statistiques d'un scan temporel, et un scan avec l'algorithme «Qu'y a-t-il d'étrange avec des évènements récents?¼ (WSARE). Les tendances d'AMR variaient entre les antibiotiques pour un agent pathogène et entre les agents pathogènes pour un antibiotique unique, ce qui suggère que la surveillance AMR pour un agent pathogène spécifique serait préférable à des données indicatrices. Les quatre méthodes ont fourni des données complémentaires, et parfois des résultats redondants. La combinaison la plus appropriée de méthodes d'analyse pour la surveillance en utilisant ces données incluait les statistiques d'un scan temporel avec une méthode de visualisation (moyenne mobile ou graphes de probabilité prédite suite à des modèles de régression logistique). L'algorithme WSARE a fourni des résultats intéressants pour le contrôle de qualité et a le potentiel de détecter des nouveaux patrons de résistance; toutefois, des données manquantes ont causé des problèmes pour montrer les résultats d'une manière qui serait signifiante pour toutes les personnes concernées par la surveillance.(Traduit par Docteur Serge Messier).

Antimicrobial susceptibility of Escherichia coli F4, Pasteurella multocida, and Streptococcus suis isolates from a diagnostic veterinary laboratory and recommendations for a surveillance system.

Antimicrobial susceptibility data on Escherichia coli F4, Pasteurella multocida, and Streptococcus suis isolates from Ontario swine (January 1998 to October 2010) were acquired from a comprehensive diagnostic veterinary laboratory in Ontario, Canada. In relation to the possible development of a surveillance system for antimicrobial resistance, data were assessed for ease of management, completeness, consistency, and applicability for temporal and spatial statistical analyses. Limited farm location data precluded spatial analyses and missing demographic data limited their use as predictors within multivariable statistical models. Changes in the standard panel of antimicrobials used for susceptibility testing reduced the number of antimicrobials available for temporal analyses. Data consistency and quality could improve over time in this and similar diagnostic laboratory settings by encouraging complete reporting with sample submission and by modifying database systems to limit free-text data entry. These changes could make more statistical methods available for disease surveillance and cluster detection.

Sensibilité antimicrobienne des isolats d'Escherichia coliF4, dePasteurella multocidaet deStreptococcus suistransmise par un laboratoire de diagnostic vétérinaire et recommandations pour un système de surveillance. Les données de sensibilité antimicrobienne sur les isolats d'Escherichia coli F4, de Pasteurella multocida et de Streptococcus suis provenant des porcs de l'Ontario (de janvier 1998 à octobre 2010) ont été acquises auprès d'un laboratoire de diagnostic vétérinaire complet situé en Ontario, au Canada. En relation avec la création éventuelle d'un système de surveillance pour l'antibiorésistance, des données ont été évaluées pour déterminer la facilité de gestion, l'intégralité, la cohérence et l'applicabilité des analyses temporelles et spatiales. Des données limitées sur l'emplacement de la ferme empêchaient des analyses spatiales et des données démographiques manquantes limitaient leur utilisation comme prédicteurs au sein de modèles statistiques multivariables. Les changements du groupe standard d'antimicrobiens utilisés pour les tests de sensibilité ont réduit le nombre d'antimicrobiens disponibles pour des analyses temporelles. La cohérence et la qualité des données pourraient être améliorées au fil du temps dans ce laboratoire de diagnostic et d'autres installations semblables en encourageant la production de rapports complets avec la soumission d'échantillons et en modifiant les systèmes des bases de données afin de limiter l'entrée de données en forme libre. Ces changements pourraient rendre d'autres méthodes statistiques disponibles pour la surveillance des maladies et la détection de grappes.(Traduit par Isabelle Vallières).

Assessment of seasonality of influenza in swine using field submissions to a diagnostic laboratory in Ontario between 2007 and 2012.

BACKGROUND: Seasonality of any infectious disease is important for its control and monitoring. While influenza seasonality in people has been evaluated extensively, this question has not been studied well in swine populations. OBJECTIVE: The goal of this study was to investigate seasonality of influenza in swine, using diagnostic submissions to a diagnostic laboratory. METHODS: Two thousand seven hundred and eleven virological tests within 685 submissions and 5471 serological tests within 193 submissions in Ontario swine between 2007 and 2012 were included in the study and converted to total monthly number of virological and serological submissions, and the number of positive submissions. Data were analyzed by time-series decomposition, fixed-effect Poisson, random-effect Poisson regression with month as uncorrelated and correlated random effects. RESULTS: All approaches identified seasonality in virological submissions (P < 0.02) with peak in January and April, and a trough in July, but were not able to detect seasonality of influenza-positive virological submissions (P > 0.13). Seasonality of positive serological submissions was identified only if independence between months was assumed (P < 0.03). Almost 50% of serological submissions had evidence of exposure to H3N2 and H1N1. CONCLUSIONS: Thus, this study identified evidence of seasonality in influenza-like disease in swine herds, but not in circulation of influenza virus. Evidence of seasonality in exposure to influenza was dependent on assumptions of between-month correlation. High exposure to H3N2 and H1N1 subtypes warrants more detailed investigation of within-herd influenza virus circulation. The study provides initial insight into seasonality of influenza in swine and should be followed with herd-level studies.

Multiple-class antimicrobial resistance surveillance in swine Escherichia coli F4, Pasteurella multocida and Streptococcus suis isolates from Ontario and the impact of the 2004-2006 Porcine Circovirus type-2 Associated Disease outbreak.

The objective of this work was to describe trends in multiple-class antimicrobial resistance present in clinical isolates of Escherichia coli F4, Pasteurella multocida and Streptococcus suis from Ontario swine 1998-2010. Temporal changes in multiple-class resistance varied by the pathogens examined; significant yearly changes were apparent for the E. coli and P. multocida data. Although not present in the E. coli data, significant increases in multiple-class resistance within P. multocida isolates occurred from 2003 to 2005, coinciding with the expected increase in antimicrobials used to treat clinical signs of Porcine Circovirus Associated Disease (PCVAD) before it was confirmed. Prospective temporal scan statistics for multiple-class resistance suggest that significant clusters of increased resistance may have been found in the spring of 2004; months before the identification of the PCVAD outbreak in the fall of 2004.

Describing antimicrobial use and reported treatment efficacy in Ontario swine using the Ontario Swine Veterinary-based Surveillance program.

BACKGROUND: The objective of this work was to retrospectively assess records received through the Ontario Swine Veterinary-based Surveillance program July 2007 - July 2009 to describe and assess relationships between reported treatment failure, antimicrobial use, diagnosis and body system affected. RESULTS: Antimicrobial use occurred in 676 records, 80.4% of all records recording treatment (840). The most commonly used antimicrobials were penicillin (34.9%), tetracyclines (10.7%) and ceftiofur (7.8%), and the use of multiple antimicrobials occurred in 141/676 records (20.9%). A multi-level logistic regression model was built to describe the probability of reported treatment failure. The odds of reported treatment failure were significantly reduced if the record indicated that the gastro-intestinal (GI) system was affected, as compared to all other body systems (p < 0.05). In contrast, the odds of reported treatment failure increased by 1.98 times if two antimicrobials were used as compared to one antimicrobial (p = 0.009) and by 6.52 times if three or more antimicrobials were used as compared to one antimicrobial (p = 0.005). No significant increase in reported treatment failure was seen between the use of two antimicrobials and three or more antimicrobials. No other antimicrobials were significantly associated with reported treatment failure after controlling for body system and the number of antimicrobials used. CONCLUSIONS: Failure of antimicrobial treatment is more likely to occur in non-GI conditions, as compared to GI conditions and the use of multiple antimicrobial products is also associated with an increased probability of antimicrobial treatment failure. The authors suggest that a more preventative approach to herd health should be taken in order to reduce antimicrobial inputs on-farm, including improved immunity via vaccination, management and biosecurity strategies. Furthermore, improved immunity may be viewed as a form of antimicrobial stewardship to the industry by reducing required antimicrobial inputs and consequently, reduced selection pressure for AMR.

Syndromic surveillance using veterinary laboratory data: algorithm combination and customization of alerts.

BACKGROUND: Syndromic surveillance research has focused on two main themes: the search for data sources that can provide early disease detection; and the development of efficient algorithms that can detect potential outbreak signals. METHODS: This work combines three algorithms that have demonstrated solid performance in detecting simulated outbreak signals of varying shapes in time series of laboratory submissions counts. These are: the Shewhart control charts designed to detect sudden spikes in counts; the EWMA control charts developed to detect slow increasing outbreaks; and the Holt-Winters exponential smoothing, which can explicitly account for temporal effects in the data stream monitored. A scoring system to detect and report alarms using these algorithms in a complementary way is proposed. RESULTS: The use of multiple algorithms in parallel resulted in increased system sensitivity. Specificity was decreased in simulated data, but the number of false alarms per year when the approach was applied to real data was considered manageable (between 1 and 3 per year for each of ten syndromic groups monitored). The automated implementation of this approach, including a method for on-line filtering of potential outbreak signals is described. CONCLUSION: The developed system provides high sensitivity for detection of potential outbreak signals while also providing robustness and flexibility in establishing what signals constitute an alarm. This flexibility allows an analyst to customize the system for different syndromes.

A retrospective study on the etiological diagnoses of diarrhea in neonatal piglets in Ontario, Canada, between 2001 and 2010.

Laboratory surveillance data from the Animal Health Laboratory, University of Guelph, on the etiological diagnoses of neonatal diarrhea in piglets were analyzed to determine the relative importance and trends of different enteric pathogens in Ontario. A total of 237 cases, including live and dead 1- to 7-day-old piglets, were submitted for diagnosis of gastrointestinal illness between 2001 and 2010. The combined frequencies for cases of gastrointestinal illness involving Escherichia coli, Clostridium perfringens type A, rotavirus, and Clostridium difficile, either as single pathogens or a complex of pathogens, accounted for 56% of the total cases. In a total of 33% of cases of gastrointestinal illness, an etiological agent was not identified. The frequency of cases diagnosed with enterotoxigenic E. coli was decreased from 2007. Cases submitted in 2010 were more likely to be diagnosed with C. perfringens type A compared to cases submitted in 2002 to 2007 (P < 0.05). There was a significant trend for cases submitted in the winter to be diagnosed with C. perfringens type A, enterotoxigenic E. coli, rotavirus, and Cystoisospora suis (formerly Isospora suis) (P < 0.05). Enterotoxigenic E. coli was less likely diagnosed if C. difficile, C. perfringens, or rotavirus were detected (P < 0.05). Younger piglets were more likely to be diagnosed with C. perfringens type A (P < 0.05) and C. difficile (P < 0.05) than older piglets. This study shows that E. coli, C. perfringens type A, rotavirus, and C. difficile are enteric pathogens of concern for Ontario swine farrowing operations and further research is required to understand the reasons for the cases that are not diagnosed.

Les données de surveillance provenant du Animal Health Laboratory de l'University of Guelph sur les diagnostics étiologiques des diarrhées néonatales des porcelets ont été analysées afin de déterminer l'importance relative et les tendances des différents agents pathogènes entériques en Ontario. Entre 2001 et 2010, 237 cas de porcelets vivants et morts âgés de 1 à 7 jours ont été soumis pour un diagnostic de maladie gastrointestinale. Les fréquences combinées pour les cas de maladies gastrointestinales impliquant Escherichia coli, Clostridium perfringens type A, rotavirus, et Clostridium difficile, soit comme seul agent pathogène ou un complexe d'agents pathogènes, représentaient 56 % du total des cas. Pour 33 % des cas de maladies gastrointestinales, aucun agent étiologique n'a été identifié. La fréquence des cas avec un diagnostic d'E. coli entérotoxigénique a diminué à compter de 2007. Les cas soumis en 2010 étaient plus susceptibles d'avoir un diagnostic d'infection à C. perfringens type A comparativement aux cas soumis de 2002 à 2007 (P < 0,05). Il y avait une tendance significative pour les cas soumis en hiver d'avoir un diagnostic avec C. perfringens type A, E. coli entérotoxigénique, rotavirus, et Cystoisospora suis (anciennement Isospora suis) (P < 0,05). Les E. coli entérotoxigéniques étaient moins souvent diagnostiquées si C. difficile, C. perfringens, ou du rotavirus étaient détectés (P < 0,05). Les porcelets plus jeunes étaient plus susceptibles d'être diagnostiqués avec du C. perfringens type A (P < 0,05) et C. difficile (P < 0,05) que les porcelets plus vieux. Cette étude démontre que E. coli, C. perfringens type A, rotavirus, et C. difficile sont des agents pathogènes d'intérêt pour les opérations de mise-bas en Ontario et des recherches supplémentaires sont requises pour comprendre les raisons pour lesquelles certains cas ne sont pas diagnostiqués.(Traduit par Docteur Serge Messier).

Syndromic surveillance using veterinary laboratory data: data pre-processing and algorithm performance evaluation.

Diagnostic test orders to an animal laboratory were explored as a data source for monitoring trends in the incidence of clinical syndromes in cattle. Four years of real data and over 200 simulated outbreak signals were used to compare pre-processing methods that could remove temporal effects in the data, as well as temporal aberration detection algorithms that provided high sensitivity and specificity. Weekly differencing demonstrated solid performance in removing day-of-week effects, even in series with low daily counts. For aberration detection, the results indicated that no single algorithm showed performance superior to all others across the range of outbreak scenarios simulated. Exponentially weighted moving average charts and Holt-Winters exponential smoothing demonstrated complementary performance, with the latter offering an automated method to adjust to changes in the time series that will likely occur in the future. Shewhart charts provided lower sensitivity but earlier detection in some scenarios. Cumulative sum charts did not appear to add value to the system; however, the poor performance of this algorithm was attributed to characteristics of the data monitored. These findings indicate that automated monitoring aimed at early detection of temporal aberrations will likely be most effective when a range of algorithms are implemented in parallel.

A prospective study of sheep and goat abortion using real-time polymerase chain reaction and cut point estimation shows Coxiella burnetii and Chlamydophila abortus infection concurrently with other major pathogens.

From 2009 to 2011, 163 sheep and 96 goat abortion submissions were received at the Animal Health Laboratory, University of Guelph, Ontario, Canada, for gross and histologic examination, as well as real-time polymerase chain reaction (PCR) testing for Chlamydophila abortus and/or Coxiella burnetii. Additional testing included immunohistochemistry for Toxoplasma gondii and Chlamydophila spp., routine bacterial culture and selective culture for Campylobacter spp., examination of modified acid-fast-stained placenta smears, enzyme-linked immunosorbent assay testing for Chlamydophila spp., and virus isolation. The final diagnosis made for each case by individual pathologists, based on gross and histologic lesions, as well as ancillary testing, was used as a standard to determine the significance of C. abortus and C. burnetii infection. Coxiella burnetii was identified by real-time PCR in 113 of 163 (69.0%) and 72 of 96 (75%) sheep and goat abortion submissions, respectively, but was considered to be significant in causing abortion in only 11 of 113 (10%) sheep and 15 out of 72 (21%) goat submissions that tested positive. Chlamydophila abortus was identified by real-time PCR in 42 of 162 (26%) and 54 of 92 (59%) sheep and goat submissions, respectively, but was considered the cause of the abortion in 16 of 42 (38%) sheep and 34 of 54 (63%) goat submissions that tested positive. Optimal sensitivity and specificity cut points for the real-time PCR copy number for C. abortus and C. burnetii were determined using the final pathology diagnosis as the reference test.

Exploratory analysis of methods for automated classification of laboratory test orders into syndromic groups in veterinary medicine.

BACKGROUND: Recent focus on earlier detection of pathogen introduction in human and animal populations has led to the development of surveillance systems based on automated monitoring of health data. Real- or near real-time monitoring of pre-diagnostic data requires automated classification of records into syndromes--syndromic surveillance--using algorithms that incorporate medical knowledge in a reliable and efficient way, while remaining comprehensible to end users. METHODS: This paper describes the application of two of machine learning (Naïve Bayes and Decision Trees) and rule-based methods to extract syndromic information from laboratory test requests submitted to a veterinary diagnostic laboratory. RESULTS: High performance (F1-macro = 0.9995) was achieved through the use of a rule-based syndrome classifier, based on rule induction followed by manual modification during the construction phase, which also resulted in clear interpretability of the resulting classification process. An unmodified rule induction algorithm achieved an F(1-micro) score of 0.979 though this fell to 0.677 when performance for individual classes was averaged in an unweighted manner (F(1-macro)), due to the fact that the algorithm failed to learn 3 of the 16 classes from the training set. Decision Trees showed equal interpretability to the rule-based approaches, but achieved an F(1-micro) score of 0.923 (falling to 0.311 when classes are given equal weight). A Naïve Bayes classifier learned all classes and achieved high performance (F(1-micro)= 0.994 and F(1-macro) = .955), however the classification process is not transparent to the domain experts. CONCLUSION: The use of a manually customised rule set allowed for the development of a system for classification of laboratory tests into syndromic groups with very high performance, and high interpretability by the domain experts. Further research is required to develop internal validation rules in order to establish automated methods to update model rules without user input.

Retrospective time series analysis of veterinary laboratory data: preparing a historical baseline for cluster detection in syndromic surveillance.

The practice of disease surveillance has shifted in the last two decades towards the introduction of systems capable of early detection of disease. Modern biosurveillance systems explore different sources of pre-diagnostic data, such as patient's chief complaint upon emergency visit or laboratory test orders. These sources of data can provide more rapid detection than traditional surveillance based on case confirmation, but are less specific, and therefore their use poses challenges related to the presence of background noise and unlabelled temporal aberrations in historical data. The overall goal of this study was to carry out retrospective analysis using three years of laboratory test submissions to the Animal Health Laboratory in the province of Ontario, Canada, in order to prepare the data for use in syndromic surveillance. Daily cases were grouped into syndromes and counts for each syndrome were monitored on a daily basis when medians were higher than one case per day, and weekly otherwise. Poisson regression accounting for day-of-week and month was able to capture the day-of-week effect with minimal influence from temporal aberrations. Applying Poisson regression in an iterative manner, that removed data points above the predicted 95th percentile of daily counts, allowed for the removal of these aberrations in the absence of labelled outbreaks, while maintaining the day-of-week effect that was present in the original data. This resulted in the construction of time series that represent the baseline patterns over the past three years, free of temporal aberrations. The final method was thus able to remove temporal aberrations while keeping the original explainable effects in the data, did not need a training period free of aberrations, had minimal adjustment to the aberrations present in the raw data, and did not require labelled outbreaks. Moreover, it was readily applicable to the weekly data by substituting Poisson regression with moving 95th percentiles.

Identifying an outbreak of a novel swine disease using test requests for porcine reproductive and respiratory syndrome as a syndromic surveillance tool.

BACKGROUND: Animal disease monitoring and surveillance are crucial for ensuring the health of animals, humans and the environment. Many studies have investigated the utility of monitoring syndromes associated with data from veterinary laboratory submissions, but no research has focused on how negative test results from a veterinary diagnostic laboratory data can be used to improve our knowledge of disease outbreaks. For example, if a diagnostic laboratory was seeing a disproportionate number of negative test results for a known disease could this information be an indication of a novel disease outbreak? The objective of this study was to determine the association between the porcine circovirus associated disease (PCVAD) outbreak in Ontario 2004-2006 and the results of porcine reproductive and respiratory syndrome virus (PPRSV) enzyme-linked immunosorbent assay (ELISA) and the results of PRRSV polymerase chain reaction (PCR) diagnostic tests requested by veterinarians. RESULTS: Retrospective data were collected from the Animal Health Laboratory (AHL) at the University of Guelph, Guelph, Ontario Canada and were comprised of weekly counts of PRRSV ELISA and PRRSV PCR diagnostic tests requested by swine practitioners from 2000-2007. The results of the PRRSV ELISA and PRRSV PCRs were analysed separately in two models using logistic regression with the dependent variables being: the weekly probability of PRRSV ELISA positivity, and the weekly probability of PRRSV PCR positivity, respectively. The weekly probability of PRRSV PCR positivity decreased during the PVCAD outbreak (OR=0.66, P=0.01). The weekly probability of PRRSV ELISA positivity was not associated with the PCVAD outbreak. CONCLUSIONS: The results of this study showed that during the PCVAD outbreak in Ontario from December 2004-May 2006, the probability of a positive PRRSV PCR at the AHL decreased. We conclude that when a decrease in test positivity occurs for a known disease, it may suggest that a new disease agent is emerging in the population. Hence, monitoring the test results of commonly used first-order tests for a known disease (e.g. PRRSV) has the potential to be a unique form of syndromic data for the timely identification of novel disease outbreaks in swine populations.

Evaluation of experimental impact injury for inducing post-traumatic osteoarthritis in the metacarpophalangeal joints of horses.

OBJECTIVE: To determine whether a single contusive impact injury to the palmar aspect of the metacarpus would progress to post-traumatic osteoarthritis or palmar osteochondral disease in horses. ANIMALS: 12 horses. PROCEDURES: In each horse, an impact injury was created on the palmar aspect of the medial metacarpal condyle of 1 randomly chosen limb with an impactor device under arthroscopic and fluoroscopic guidance. The opposite limb was sham operated as a control. A low to moderate amount of forced exercise was instituted, and horses were evaluated clinically via lameness examinations weekly for 5 months, then biweekly until endpoint, with synovial fluid analysis performed at 0, 1, 2, 3, 4, 6, 8, and 10 months and radiography at baseline and endpoint. Macroscopic examination, micro-CT, and sample collection for cartilage viability and sulfated glycosaminoglycan content, histologic evaluation, immunohistochemical analysis, and fluorochrome analysis were performed following euthanasia at 1 (3 horses), 4 (4), and 8 to 10 (5) months after surgery. RESULTS: There was variability in impact lesion location, depth, and area on macroscopic inspection, but on histologic evaluation, cartilage defects were less variable. Mean sulfated glycosaminoglycan concentration from cartilage at the impact site was significantly lower than that at a similar site in control limbs. Higher concentrations of cartilage oligomeric matrix protein were observed in synovial fluid from impact-injured joints. CONCLUSIONS AND CLINICAL RELEVANCE: The impact injury method caused mild focal osteoarthritic lesions in the metacarpophalangeal joint, but did not progress to palmar osteochondral disease at this site. Repeated injury is probably required for the development of palmar osteochondral disease.

Clinical and MRI findings in three dogs with polycystic meningiomas.

One spayed female Labrador retriever and two castrated male golden retrievers were evaluated for chronic (i.e., ranging from 3 wk to 24 wk) neurologic signs localizable to the prosencephalon. Signs included seizures, circling, and behavior changes. MRI demonstrated extra-axial, contrast-enhancing, multiloculated, fluid-filled, cyst-like lesions with a mass effect, causing compression and displacement of brain parenchyma. Differential diagnoses included cystic neoplasm, abscess or other infectious cyst (e.g., alveolar hydatid cyst), or fluid-filled anomaly (e.g., arachnoid cyst). The cyst-like lesions were attached to the rostral falx cerebri in all cases. In addition, case 2 had a second polycystic mass at the caudal diencephalon. Surgical biopsy (case 3 with a single, rostral tumor via transfrontal craniectomy) and postmortem histology (in cases 1 and 2) confirmed polycystic meningiomas. Tumor types were transitional (cases 1 and 3) and fibrous (case 2), with positive immunohistochemical staining for vimentin. Case 3 was also positive for E-cadherin, s100, and CD34. In all cases, staining was predominantly negative for glial fibrillary acid protein and pancytokeratins, supporting a diagnosis of meningioma. This report describes the first cases of polycystic meningiomas in dogs. Polycystic meningiomas are a rare, but important, addition to the differential diagnoses for intracranial cyst-like lesions, significantly affecting planning for surgical resection and other therapeutic interventions.

Trends in domestic animal medico-legal pathology cases submitted to a veterinary diagnostic laboratory 1998-2010.

Pathologists at veterinary diagnostic laboratories receive medico-legal cases from a variety of animal species for postmortem examination. A search of computerized records of the Animal Health Laboratory, University of Guelph, Guelph, Ontario, Canada from 1998 to 2010 identified 1706 medicolegal cases. These were categorized according to the history as criminal investigations, anesthetic-related deaths, insurance, litigation, malpractice cases, and regulatory cases. Statistically significant linear trends in the proportion of medicolegal cases for all animals and criminal cases for companion animals were identified over the 12 year period. Companion animals had significantly greater odds of being a medicolegal case in all categories except for insurance and regulatory cases, compared to noncompanion animals. Based on pathology reports for the 271 criminal cases, 43.1% were consistent with neglect, 29.2% were compatible with non-accidental injury, 4.80% were poisonings, 10.7% were deemed to be due to natural disease, and 11.43% were inconclusive.