The value of necropsy reports for animal health surveillance

Pathological investigation of high pathogenicity avian influenza H5N8 in captive houbara bustards (Chlamydotis undulata), the United Arab Emirates 2020

At the end of 2020, an outbreak of HPAI H5N8 was registered in captive African houbara bustards (Chlamydotis undulata) in the United Arab Emirates. In order to better understand the pathobiology of this viral infection in bustards, a comprehensive pathological characterization was performed. A total of six birds were selected for necropsy, histopathology, immunohistochemistry, RNAscope in situ hybridization and RT-qPCR and nanopore sequencing on formalin-fixed and paraffin-embedded (FFPE) tissue blocks. Gross lesions included mottled and/or hemorrhagic pancreas, spleen and liver and fibrinous deposits on air sacs and intestine. Necrotizing pancreatitis, splenitis and concurrent vasculitis, hepatitis and fibrino-heterophilic peritonitis were identified, microscopically. Viral antigens (nucleoprotein) and RNAs (matrix gene) were both detected within necro-inflammatory foci, parenchymal cells, stromal cells and endothelial cells of affected organs, including the myenteric plexus. Molecular analysis of FFPE blocks successfully detected HPAI H5N8, further confirming its involvement in the lesions observed. In conclusion, HPAI H5N8 in African houbara bustards results in hyperacute/acute forms exhibiting marked pantropism, endotheliotropism and neurotropism. In addition, our findings support the use of FFPE tissues for molecular studies of poorly characterized pathogens in exotic and endangered species, when availability of samples is limited.

Strategies for Bovine Respiratory Disease (BRD) Diagnosis and Prognosis: A Comprehensive Overview

Despite significant advances in vaccination strategies and antibiotic therapy, bovine respiratory disease (BRD) continues to be the leading disease affecting the global cattle industry. The etiology of BRD is complex, often involving multiple microbial agents, which lead to intricate interactions between the host immune system and pathogens during various beef production stages. These interactions present environmental, social, and geographical challenges. Accurate diagnosis is essential for effective disease management. Nevertheless, correct identification of BRD cases remains a daunting challenge for animal health technicians in feedlots. In response to current regulations, there is a growing interest in refining clinical diagnoses of BRD to curb the overuse of antimicrobials. This shift marks a pivotal first step toward establishing a structured diagnostic framework for this disease. This review article provides an update on recent developments and future perspectives in clinical diagnostics and prognostic techniques for BRD, assessing their benefits and limitations. The methods discussed include the evaluation of clinical signs and animal behavior, biomarker analysis, molecular diagnostics, ultrasound imaging, and prognostic modeling. While some techniques show promise as standalone diagnostics, it is likely that a multifaceted approach-leveraging a combination of these methods-will yield the most accurate diagnosis of BRD.

Morbidity and Prognostic Factors Associated with Wild Hedgehogs Admitted to a Wildlife Rehabilitation Center in Catalonia (NE Spain) from 1995 to 2020

Wildlife rehabilitation centers (WRC) play a crucial role in the collection of data and the monitoring of hedgehog populations. The main objective of this study was to identify the morbidity and prognostic factors associated with the mortality of wild hedgehogs admitted at a WRC in Catalonia. A total number of 3397 hedgehogs admitted from 1995 to 2020 were studied. The principal cause of admission was orphaned/young category (41%) followed by misplacement (19%), natural disease (17%), and trauma (14%). The best outcomes for release were for misplacement (93.6%), orphaned/young (72.3%), and other causes (77.6%), and the lowest proportion of released animals were found for natural disease (41.4%) and trauma (44.7%) categories. The most common macroscopic findings were the respiratory and digestive lesions. Internal parasites were also prevalent in 61% of the animals but with no association with a higher mortality. In the multivariate analyses, the prognostic indicators related with the mortality outcome were the presence of systemic (OR = 3.6, CI 95%: 2.8-4.6) and neurological (OR = 4.3, CI 95%: 2.9-6.4) signs. Morbidity and prognostic factors in wildlife rehabilitation are essential for providing effective care, making informed decisions, optimizing resources, and improving rehabilitation success rates.

Lesions and pathogens found in pigs that died during the nursery period in five Danish farms

BACKGROUND

Diagnosing and treatment of diseases in pigs are important to maintain animal welfare, food safety and productivity. At the same time antimicrobial resistance is increasing, and therefore, antibiotic treatment should be reserved for individuals with a bacterial infection. The aim of the study was to investigate gross and histological lesions and related pathogens in pigs that died during the nursery period in five Danish farms. In addition, high throughput, real-time qPCR monitoring of specific porcine pathogens in fecal sock and oral fluid samples were carried out to investigate the between-farm and between-batch variation in the occurrence of pathogens.

RESULTS

Twenty-five batches of nursery pigs from five intensive, indoor herds were followed from weaning (approximately four weeks) to the end of nursery (seven to eight weeks post weaning). Gross and histological evaluation of 238 dead and 30 euthanized pigs showed the highest prevalence of lesions in the skin, respiratory system, gastrointestinal tract, and joints. Gross and histological diagnoses of lung and joint lesions agreed in 46.5% and 62.2% of selected pigs, respectively. Bacteriological detection of Escherichia coli, Streptococcus suis or Staphylococcus aureus infections in joints, lungs and livers was confirmed as genuine infection on immunohistochemical staining in 11 out of 70 tissue sections. The real-time qPCR analysis of pooled samples showed that most pathogens detected in feces and in oral fluid in general followed the same shedding patterns in consecutive batches within herds.

CONCLUSIONS

Gross assessment should be supplemented with a histopathological assessment especially when diagnosing lesions in the lungs and joints. Moreover, microbiological detection of pathogens should optimally be followed up by in situ identification to confirm causality. Furthermore, routine necropsies can reveal gastric lesions that may warrant a change in management. Real-time qPCR testing of fecal sock samples and oral fluid samples may be used to monitor the infections in the individual herd and testing one batch seems to have a good predictive value for subsequent batches within a herd. Overall, optimal diagnostic protocols will provide a more substantiated prescription of antibiotics.

Image Classification and Automated Machine Learning to Classify Lung Pathologies in Deceased Feedlot Cattle

Bovine respiratory disease (BRD) and acute interstitial pneumonia (AIP) are the main reported respiratory syndromes (RSs) causing significant morbidity and mortality in feedlot cattle. Recently, bronchopneumonia with an interstitial pattern (BIP) was described as a concerning emerging feedlot lung disease. Necropsies are imperative to assist lung disease diagnosis and pinpoint feedlot management sectors that require improvement. However, necropsies can be logistically challenging due to location and veterinarians' time constraints. Technology advances allow image collection for veterinarians' asynchronous evaluation, thereby reducing challenges. This study's goal was to develop image classification models using machine learning to determine RS diagnostic accuracy in right lateral necropsied feedlot cattle lungs. Unaltered and cropped lung images were labeled using gross and histopathology diagnoses generating four datasets: unaltered lung images labeled with gross diagnoses, unaltered lung images labeled with histopathological diagnoses, cropped images labeled with gross diagnoses, and cropped images labeled with histopathological diagnoses. Datasets were exported to create image classification models, and a best trial was selected for each model based on accuracy. Gross diagnoses accuracies ranged from 39 to 41% for unaltered and cropped images. Labeling images with histopathology diagnoses did not improve average accuracies; 34-38% for unaltered and cropped images. Moderately high sensitivities were attained for BIP (60-100%) and BRD (20-69%) compared to AIP (0-23%). The models developed still require fine-tuning; however, they are the first step towards assisting veterinarians' lung diseases diagnostics in field necropsies.

A Minimally Invasive, Accurate, and Efficient Technique for Intrathymic Injection in Mice

Intrathymic injection in mouse models is an important technique for studying thymic and immune function, including genetic and acquired T cell disorders. This requires methods for the direct deposition of reagents and/or cells into the thymus of living mice. Traditional methods of intrathymic injection include thoracic surgery or minimally invasive percutaneous blind injections, both of which have significant limitations. Ultra-high frequency ultrasound imaging devices have made image-guided percutaneous injections possible in mice, greatly improving the injection accuracy of the percutaneous injection approach and enabling the injection of smaller targets. However, image-guided injections rely on the utilization of an integrated rail system, making this a rigid and time-consuming procedure. A unique, safe, and efficient method for percutaneous intrathymic injections in mice is presented here, eliminating reliance on the rail system for injections. The technique relies on using a high-resolution micro-ultrasound unit to image the mouse thymus noninvasively. Using a free-hand technique, a radiologist can place a needle tip directly into the mouse thymus under sonographic guidance. Mice are cleaned and anesthetized before imaging. For an experienced radiologist adept at ultrasound-guided procedures, the learning period for the stated technique is quite short, typically within one session. The method has a low morbidity and mortality rate for the mice and is much faster than current mechanically assisted techniques for percutaneous injection. It allows the investigator to efficiently perform precise and reliable percutaneous injections of thymuses of any size (including very small organs such as the thymus of aged or immunodeficient mice) with minimal stress on the animal. This method enables the injection of individual lobes if desired and facilities large-scale experiments due to the time-saving nature of the procedure.

Infectious Bovine Respiratory Diseases in Adult Cattle: An Extensive Necropsic and Etiological Study

Simple Summary

Animal necropsy can accurately determine the cause of its death. However, studies based on large-scale necropsies of cattle are rare because they require special skills and equipment. This study places particular emphasis on fatal respiratory diseases in adult cattle. The objectives of this study were to assess the importance of respiratory diseases as a cause of death in adult cattle and to determine associated lesions as well as associated pathogens of infectious causes of respiratory diseases in adult cattle. This study showed that respiratory diseases are the second leading cause of death in adult cattle after digestive diseases. Among respiratory diseases, we noticed a strong predominance of infectious pulmonary lesions, mainly characterized by fibrinous, hemorrhagic and/or necrotic bronchopneumonia. These bronchopneumonia are mainly associated with the detection of a bacteria, Mannheimia haemolytica. This study suggests that Mannheimia haemolytica should be included in the differential diagnosis of BRD in adult cattle.

Abstract

In young cattle, bovine respiratory disease (BRD) is a major cause of death and Mannheimia haemolytica is a frequent pathogen. Knowledge of fatal BRD in adult cattle is more limited. We assessed the importance of infectious BRD as a cause of death in adult cattle and determined the associated pathogens. We analyzed data from 737 adult cattle necropsies at the Pathology Unit for Large Animals at Oniris, Nantes, France over a 6 year period (2013–2019). Each carcass was subjected to a complete necropsy. Lungs showing macroscopic lesions were classified into three categories: infectious primary pulmonary (IPP) lesions, thromboembolic pneumonia (TEP) and others (aspiration pneumonia, verminous pneumonia, and local extension of an extra-pulmonary inflammatory process). Half of the lungs with IPP macroscopic lesions were sampled for histology and submitted for polymerase chain reaction. BRD was the second leading cause of death (15.7%) after digestive diseases (32.2%). A strong predominance of IPP lesions (42.3%) and TEP lesions (39.6%) was also demonstrated. In IPP macroscopic lesions, fibrinous, hemorrhagic and/or hecrotic (FHN) bronchopneumonia accounted for 77.6% of macroscopic lesions. Mannheimia haemolytica was significantly associated with FHN bronchopneumonia macroscopic lesions. This study suggests that Mannheimia haemolytica should be included in the differential diagnosis of BRD in adult cattle.

Existence and Quality of Data on Control Programs for EU Non-regulated Cattle Diseases: Consequences for Estimation and Comparison of the Probability of Freedom From Infection

Some European countries have successfully implemented country-specific control programs (CPs) for infectious cattle diseases that are not regulated or are regulated only to a limited extent at the European Union (EU) level. Examples of such diseases include bovine viral diarrhea (BVD), infectious bovine rhinotracheitis (IBR), and Johne's disease (JD). The CPs vary between countries in the design and quality of collected data as well as methods used to detect infection and estimate prevalence or probability of freedom from infection. Differences in disease status between countries and non-standardized approaches to assess freedom from infection pose a risk for countries with CPs for non-regulated diseases as infected animals may influence the progress of the disease control or eradication program. The implementation of output-based standards allows estimation and comparison of the probability of freedom for non-regulated cattle diseases in European countries. The aim of the current study was to assess the existence and quality of data that could be used for estimating freedom from infection in European countries. The online data collection tool was sent to 32 countries participating in the SOUND control COST Action and was completed by 24 countries. Data on cattle demographics and data from CPs of IBR and BVD exist in more than 50% of the response countries. However, data describing risk factors and CP of JD was reported as existing in <25% of the countries. The overall quality of data in the sections on demographics and CPs of IBR and BVD were evaluated as "good", but risk factors and JD data were mostly evaluated as "fair." Data quality was considered less good mainly due to two quality criteria: accessibility and accuracy. The results of this study show that the quantity and quality of data about cattle populations and CPs are relatively similar in many surveyed countries. The outcome of this work provides an overview of the current situation in the European countries regarding data on EU non-regulated cattle diseases and will further assist in the development and implementation of output-based standards.

Potential and Challenges of Community-Based Surveillance in Animal Health: A Pilot Study Among Equine Owners in Switzerland

Animal owners' potential to observe and report clinical signs, as the persons with the closest contact to their animals, is an often neglected source of information in surveillance. Allowing community members other than health care professionals, such as animal owners, to report health events can contribute to close current surveillance gaps and enhance early detection. In the present study, we tested a community-based surveillance (CBS) approach in the equine community in Switzerland. We aimed at revealing the attitudes and intentions of equine owners toward reporting clinical signs by making use of an online questionnaire. We further set up and operated an online CBS tool, named Equi-Commun. Finally, we investigated potential reasons for the lack of its use by applying qualitative telephone interviews. The majority of the respondents of the online questionnaire (65.5%, 707/1,078) answered that they could see themselves reporting clinical observations of their equine. The multivariate logistic regression analysis indicated that French-speaking equine owners and those belonging to the positive attitude cluster are more likely to report to a CBS tool. Equi-Commun operated between October 2018 and December 2019 yet received only four reports. With the addition of qualitative interviews, we identified three critical, interlinked issues that may have led to the non-use of Equi-Commun within the Swiss equine community: (1) for successfully implementing CBS, the need for surveillance within the community of interest must be given; (2) the respective population under surveillance, here the equine, needs to show enough clinical cases for owners to be able to maintain the memory of an existing tool and its possible use; and (3) targeted and high effort communication of the system is key for its success. While CBS relying only on lay animal owners, complementary to existing surveillance systems, could potentially provide a good proxy of timely surveillance data, it is questionable whether the added value of generated surveillance knowledge is in balance with efforts necessary to implement a successful system. With this study, we showcased both the potential and challenges of CBS in animal health, as this may be of relevance and guidance for future initiatives.

Research perspectives on animal health in the era of artificial intelligence

Leveraging artificial intelligence (AI) approaches in animal health (AH) makes it possible to address highly complex issues such as those encountered in quantitative and predictive epidemiology, animal/human precision-based medicine, or to study host × pathogen interactions. AI may contribute (i) to diagnosis and disease case detection, (ii) to more reliable predictions and reduced errors, (iii) to representing more realistically complex biological systems and rendering computing codes more readable to non-computer scientists, (iv) to speeding-up decisions and improving accuracy in risk analyses, and (v) to better targeted interventions and anticipated negative effects. In turn, challenges in AH may stimulate AI research due to specificity of AH systems, data, constraints, and analytical objectives. Based on a literature review of scientific papers at the interface between AI and AH covering the period 2009-2019, and interviews with French researchers positioned at this interface, the present study explains the main AH areas where various AI approaches are currently mobilised, how it may contribute to renew AH research issues and remove methodological or conceptual barriers. After presenting the possible obstacles and levers, we propose several recommendations to better grasp the challenge represented by the AH/AI interface. With the development of several recent concepts promoting a global and multisectoral perspective in the field of health, AI should contribute to defract the different disciplines in AH towards more transversal and integrative research.

Factors associated with cattle necropsy submissions in Switzerland, and their importance for surveillance

Pathology data have been reported to be important for surveillance, as they are crucial for correctly recognizing and identifying new or re-emerging diseases in animal populations. However, there are no reports in the literature of necropsy data being compared or complemented with other data. In our study, we compared cattle necropsy reports extracted from 3 laboratories with the Swiss fallen stock data and clinical data collected by the association of Swiss Cattle Breeders. The objective was to assess the completeness, validity and representativeness of the necropsy data, as well as evaluate potential factors for necropsy submission and how they can benefit animal health surveillance. Our results showed that, on average, 1% of Swiss cattle that die are submitted for post-mortem examinations. However, different factors influence cattle necropsy submissions, such as the age of the animal, the geographical location and the number of sick and/or dead animals on the farm. There was a median of five animals reported sick and two animals reported dead within 30 days prior to a necropsy submission, providing quantitative evidence of a correlation between on farm morbidity/mortality and post-mortem examination. Our results also showed that necropsy data can help improve the accuracy and completeness of health data for surveillance systems. In this study, we were able to demonstrate the importance of veterinary pathology data for AHS by providing quantitative evidence that necropsied animals are indicative of farms with important disease problems and are therefore critically important for surveillance. Furthermore, thanks to the amount of information provided by combined data sources, the epidemiology (e.g. season, geographic region, risk factors) of potential diseases can be analysed more precisely and help supporting animal health surveillance systems.

Federation of European Laboratory Animal Science Associations recommendations of best practices for the health management of ruminants and pigs used for scientific and educational purposes

Most ruminants and pigs used for scientific and educational aims are bred not for these purposes but in a farm environment. Given the wide range of diseases that these species might have, ensuring that the animals' health status is appropriate can be complex and challenging. The Federation of European Laboratory Animal Science Associations has previously published recommendations for the health monitoring of experimental colonies of pigs (1998) and, respectively, calves, sheep and goats (2000). Unfortunately, the uptake of those recommendations was poor and insufficiently reported in scientific publications. These new recommendations for best practice focus on the main species of ruminants (cattle, sheep and goats) and pigs. They provide general and specific information helpful for designing a health management programme for the suppliers and for the user establishments, as well as guidance on animal procurement. Critical thinking based on the fields of use of the animals is promoted, aiming to help in taking informed decisions rather than establishing an exhaustive exclusion list for pathogens. Implementing the best health and welfare management practices should be done under the guidance of a competent attending veterinarian, with expertise and sufficient authority to take the appropriate action, doubled by excellent communication skills. It is strongly recommended that the user establishment's veterinarian works in close collaboration with the supplier's veterinarian.

Machine learning for syndromic surveillance using veterinary necropsy reports

The use of natural language data for animal population surveillance represents a valuable opportunity to gather information about potential disease outbreaks, emerging zoonotic diseases, or bioterrorism threats. In this study, we evaluate machine learning methods for conducting syndromic surveillance using free-text veterinary necropsy reports. We train a system to detect if a necropsy report from the Wisconsin Veterinary Diagnostic Laboratory contains evidence of gastrointestinal, respiratory, or urinary pathology. We evaluate the performance of several machine learning algorithms including deep learning with a long short-term memory network. Although no single algorithm was superior, random forest using feature vectors of TF-IDF statistics ranked among the top-performing models with F1 scores of 0.923 (gastrointestinal), 0.960 (respiratory), and 0.888 (urinary). This model was applied to over 33,000 necropsy reports and was used to describe temporal and spatial features of diseases within a 14-year period, exposing epidemiological trends and detecting a potential focus of gastrointestinal disease from a single submitting producer in the fall of 2016.

Applied Veterinary Informatics: Development of a Semantic and Domain-Specific Method to Construct a Canine Data Repository

Animals are used to study the pathogenesis of various human diseases, but typically as animal models with induced disease. However, companion animals develop disease spontaneously in a way that mirrors disease development in humans. The purpose of this study is to develop a semantic and domain-specific method to enable construction of a data repository from a veterinary hospital that would be useful for future studies. We developed a two-phase method that combines semantic and domain-specific approaches to construct a canine data repository of clinical data collected during routine care at the Matthew J Ryan Veterinary Hospital of the University of Pennsylvania (PennVet). Our framework consists of two phases: (1) a semantic data-cleaning phase and (2) a domain-specific data-cleaning phase. We validated our data repository using a gold standard of known breed predispositions for certain diseases (i.e., mitral valve disease, atrial fibrillation and osteosarcoma). Our two-phase method allowed us to maximize data retention (99.8% of data retained), while ensuring the quality of our result. Our final population contained 84,405 dogs treated between 2000 and 2017 from 194 distinct dog breeds. We observed the expected breed associations with mitral valve disease, atrial fibrillation, and osteosarcoma (P < 0.05) after adjusting for multiple comparisons. Precision ranged from 60.0 to 83.3 for the three diseases (avg. 74.2) and recall ranged from 31.6 to 83.3 (avg. 53.3). Our study describes a two-phase method to construct a clinical data repository using canine data obtained during routine clinical care at a veterinary hospital.

Resumeq: A Novel Way of Monitoring Equine Diseases Through the Centralization of Necropsy Data

The French surveillance network for causes of equine mortality (Resumeq) was created in 2015 for the qualitative surveillance of equine mortality through the centralization in a national database of necropsy data and their subsequent epidemiological analysis. It was designed to identify the causes of equine mortality, monitor their evolution over time and space, and detect emerging diseases as early as possible. Resumeq is an event-based surveillance system involving various players and structures. It is organized around a steering body, a scientific and technical support committee and a coordination unit. Different tools have been developed specifically for Resumeq. These include standardized necropsy protocols, a thesaurus for the anatomopathological terms and the causes of equine death, and an interactive web application so that network contributors can display data analysis results. The four French veterinary schools, seventeen veterinary laboratories, and ten veterinary clinics already contribute to the production and centralization of standardized data. To date, the data from around 1,000 equine necropsies have been centralized. While most deaths were located in western France, the geographic coverage is gradually improving. Data analysis allows the main causes of death to be ranked and major threats identified on a local, regional or national level. Initial results demonstrate the feasibility and benefits of this national surveillance tool. Moreover, in the future, this surveillance could take an international dimension if several countries decided to jointly capitalize on their necropsy data.