Using examination performance data and focus groups to inform teaching - a case study from final year students of veterinary medicine.

BACKGROUND: Student feedback has played an important role in the maintenance of quality and standards in higher education. Perhaps the most commonly used method to capture feedback is a series of questions or statements where students indicate their degree of satisfaction or agreement. Focus groups offer an alternative means of capturing 'richer' qualitative data relating to students' thoughts on course structure. Aside from student evaluations, student examination performance has been used as a method to evaluate the efficacy of curriculum changes at programme level. However, this data is utilised less so at a 'finer detail' level to identify specific issues with the delivery of teaching. CASE PRESENTATION: The purpose of this report was to outline the approach taken using qualitative and quantitative data to identify problems with a specific area of teaching, inform a new teaching approach and to assess the impact of those changes. Following quantitative and qualitative analysis, a practical class on dairy herd fertility performance was highlighted as an area for improvement. After the introduction of the newly formatted practical class with a greater focus on self-directed learning, there was a significant increase in the average score (p < 0.001) and a decrease in the proportion of students failing (p < 0.001) the question that assessed the analysis of dairy herd fertility data. In addition, the R-squared value between students' performance in the fertility question and their performance in the overall examination increased from 0.06 to 0.11. CONCLUSIONS: The combination of qualitative focus group data and quantitative analysis of examination performance data represent robust methods for identifying problems associated with specific aspects of veterinary teaching.

Genome-wide association study of endo-parasite phenotypes using imputed whole-genome sequence data in dairy and beef cattle.

BACKGROUND: Quantitative genetic studies suggest the existence of variation at the genome level that affects the ability of cattle to resist to parasitic diseases. The objective of the current study was to identify regions of the bovine genome that are associated with resistance to endo-parasites. METHODS: Individual cattle records were available for Fasciola hepatica-damaged liver from 18 abattoirs. Deregressed estimated breeding values (EBV) for F. hepatica-damaged liver were generated for genotyped animals with a record for F. hepatica-damaged liver and for genotyped sires with a least one progeny record for F. hepatica-damaged liver; 3702 animals were available. In addition, individual cow records for antibody response to F. hepatica on 6388 genotyped dairy cows, antibody response to Ostertagia ostertagi on 8334 genotyped dairy cows and antibody response to Neospora caninum on 4597 genotyped dairy cows were adjusted for non-genetic effects. Genotypes were imputed to whole-sequence; after edits, 14,190,141 single nucleotide polymorphisms (SNPs) and 16,603,644 SNPs were available for cattle with deregressed EBV for F. hepatica-damaged liver and cows with an antibody response to a parasitic disease, respectively. Association analyses were undertaken using linear regression on one SNP at a time, in which a genomic relationship matrix accounted for the relationships between animals. RESULTS: Genomic regions for F. hepatica-damaged liver were located on Bos taurus autosomes (BTA) 1, 8, 11, 16, 17 and 18; each region included at least one SNP with a p value lower than 10-6. Five SNPs were identified as significant (q value < 0.05) for antibody response to N. caninum and were located on BTA21 or 25. For antibody response to F. hepatica and O. ostertagi, six and nine quantitative trait loci (QTL) regions that included at least one SNP with a p value lower than 10-6 were identified, respectively. Gene set enrichment analysis revealed a significant association between functional annotations related to the olfactory system and QTL that were suggestively associated with endo-parasite phenotypes. CONCLUSIONS: A number of novel genomic regions were suggestively associated with endo-parasite phenotypes across the bovine genome and two genomic regions on BTA21 and 25 were associated with antibody response to N. caninum.

Schmallenberg virus: a systematic international literature review (2011-2019) from an Irish perspective.

In Autumn 2011, nonspecific clinical signs of pyrexia, diarrhoea, and drop in milk yield were observed in dairy cattle near the German town of Schmallenberg at the Dutch/German border. Targeted veterinary diagnostic investigations for classical endemic and emerging viruses could not identify a causal agent. Blood samples were collected from animals with clinical signs and subjected to metagenomic analysis; a novel orthobunyavirus was identified and named Schmallenberg virus (SBV). In late 2011/early 2012, an epidemic of abortions and congenital malformations in calves, lambs and goat kids, characterised by arthrogryposis and hydranencephaly were reported in continental Europe. Subsequently, SBV RNA was confirmed in both aborted and congenitally malformed foetuses and also in Culicoides species biting midges. It soon became evident that SBV was an arthropod-borne teratogenic virus affecting domestic ruminants. SBV rapidly achieved a pan-European distribution with most countries confirming SBV infection within a year or two of the initial emergence. The first Irish case of SBV was confirmed in the south of the country in late 2012 in a bovine foetus. Since SBV was first identified in 2011, a considerable body of scientific research has been conducted internationally describing this novel emerging virus. The aim of this systematic review is to provide a comprehensive synopsis of the most up-to-date scientific literature regarding the origin of SBV and the spread of the Schmallenberg epidemic, in addition to describing the species affected, clinical signs, pathogenesis, transmission, risk factors, impact, diagnostics, surveillance methods and control measures. This review also highlights current knowledge gaps in the scientific literature regarding SBV, most notably the requirement for further research to determine if, and to what extent, SBV circulation occurred in Europe and internationally during 2017 and 2018. Moreover, recommendations are also made regarding future arbovirus surveillance in Europe, specifically the establishment of a European-wide sentinel herd surveillance program, which incorporates bovine serology and Culicoides entomology and virology studies, at national and international level to monitor for the emergence and re-emergence of arboviruses such as SBV, bluetongue virus and other novel Culicoides-borne arboviruses.

A comparison of 4 predictive models of calving assistance and difficulty in dairy heifers and cows.

The aim of this study was to build and compare predictive models of calving difficulty in dairy heifers and cows for the purpose of decision support and simulation modeling. Models to predict 3 levels of calving difficulty (unassisted, slight assistance, and considerable or veterinary assistance) were created using 4 machine learning techniques: multinomial regression, decision trees, random forests, and neural networks. The data used were sourced from 2,076 calving records in 10 Irish dairy herds. In total, 19.9 and 5.9% of calving events required slight assistance and considerable or veterinary assistance, respectively. Variables related to parity, genetics, BCS, breed, previous calving, and reproductive events and the calf were included in the analysis. Based on a stepwise regression modeling process, the variables included in the models were the dam's direct and maternal calving difficulty predicted transmitting abilities (PTA), BCS at calving, parity; calving assistance or difficulty at the previous calving; proportion of Holstein breed; sire breed; sire direct calving difficulty PTA; twinning; and 2-way interactions between calving BCS and previous calving difficulty and the direct calving difficulty PTA of dam and sire. The models were built using bootstrapping procedures on 70% of the data set. The held-back 30% of the data was used to evaluate the predictive performance of the models in terms of discrimination and calibration. The decision tree and random forest models omitted the effect of twinning and included only subsets of sire breeds. Only multinomial regression and neural networks explicitly included the modeled interactions. Calving BCS, calving difficulty PTA, and previous calving assistance ranked as highly important variables for all 4 models. The area under the receiver operating characteristic curve (ranging from 0.64 to 0.79) indicates that all of the models had good overall discriminatory power. The neural network and multinomial regression models performed best, correctly classifying 75% of calving cases and showing superior calibration, with an average error in predicted probability of 3.7 and 4.5%, respectively. The neural network and multinomial regression models developed are both suitable for use in decision-support and simulation modeling.

The creation and evaluation of a model predicting the probability of conception in seasonal-calving, pasture-based dairy cows.

Reproductive performance in pasture-based production systems has a fundamentally important effect on economic efficiency. The individual factors affecting the probability of submission and conception are multifaceted and have been extensively researched. The present study analyzed some of these factors in relation to service-level probability of conception in seasonal-calving pasture-based dairy cows to develop a predictive model of conception. Data relating to 2,966 services from 737 cows on 2 research farms were used for model development and data from 9 commercial dairy farms were used for model testing, comprising 4,212 services from 1,471 cows. The data spanned a 15-yr period and originated from seasonal-calving pasture-based dairy herds in Ireland. The calving season for the study herds extended from January to June, with peak calving in February and March. A base mixed-effects logistic regression model was created using a stepwise model-building strategy and incorporated parity, days in milk, interservice interval, calving difficulty, and predicted transmitting abilities for calving interval and milk production traits. To attempt to further improve the predictive capability of the model, the addition of effects that were not statistically significant was considered, resulting in a final model composed of the base model with the inclusion of BCS at service. The models' predictions were evaluated using discrimination to measure their ability to correctly classify positive and negative cases. Precision, recall, F-score, and area under the receiver operating characteristic curve (AUC) were calculated. Calibration tests measured the accuracy of the predicted probabilities. These included tests of overall goodness-of-fit, bias, and calibration error. Both models performed better than using the population average probability of conception. Neither of the models showed high levels of discrimination (base model AUC 0.61, final model AUC 0.62), possibly because of the narrow central range of conception rates in the study herds. The final model was found to reliably predict the probability of conception without bias when evaluated against the full external data set, with a mean absolute calibration error of 2.4%. The chosen model could be used to support a farmer's decision-making and in stochastic simulation of fertility in seasonal-calving pasture-based dairy cows.

Relative importance of herd-level risk factors for probability of infection with paratuberculosis in Irish dairy herds.

Control of paratuberculosis is challenging due to the relatively poor performance of diagnostic tests, a prolonged incubation period, and protracted environmental survival. Prioritization of herd-level interventions is not possible because putative risk factors are often not supported by risk factor studies. The objective for this study was to investigate the relative importance of risk factors for an increased probability of herd paratuberculosis infection. Risk assessment data, comprehensive animal purchase history, and diagnostic test data were available for 936 Irish dairy herds. Both logistic regression and a Bayesian ß regression on the outcome of a latent class analysis were conducted. Population attributable fractions and proportional reduction in variance explained were calculated for each variable in the logistic and Bayesian models, respectively. Routine use of the calving area for sick or lame cows was found to be a significant explanatory covariate in both models. Purchasing behavior for the previous 10 yr was not found to be significant. For the logistic model, length of time calves spend in the calving pen (25%) and routine use of the calving pen for sick or lame animals (14%) had the highest attributable fractions. For the Bayesian model, the overall R2 was 16%. Dry cow cleanliness (7%) and routine use of the calving area for sick or lame cows (6%) and had the highest proportional reduction in variance explained. These findings provide support for several management practices commonly recommended as part of paratuberculosis control programs; however, a large proportion of the observed variation in probability of infection remained unexplained, suggesting other important risks factors may exist.

An investigative framework to facilitate epidemiological thinking during herd problem-solving.

Veterinary clinicians and students commonly use diagnostic approaches appropriate for individual cases when conducting herd problem-solving. However, these approaches can be problematic, in part because they make limited use of epidemiological principles and methods, which has clear application during the investigation of herd problems. In this paper, we provide an overview of diagnostic approaches that are used when investigating individual animal cases, and the challenges faced when these approaches are directly translated from the individual to the herd. Further, we propose an investigative framework to facilitate epidemiological thinking during herd problem-solving. A number of different approaches are used when making a diagnosis on an individual animal, including pattern recognition, hypothetico-deductive reasoning, and the key abnormality method. Methods commonly applied to individuals are often adapted for herd problem-solving: 'comparison with best practice' being a herd-level adaptation of pattern recognition, and 'differential diagnoses' a herd-level adaptation of hypothetico-deductive reasoning. These approaches can be effective, however, challenges can arise. Herds are complex; a collection of individual cows, but also additional layers relating to environment, management, feeding etc. It is unrealistic to expect seamless translation of diagnostic approaches from the individual to the herd. Comparison with best practice is time-consuming and prioritisation of actions can be problematic, whereas differential diagnoses can lead to 'pathogen hunting', particularly in complex cases. Epidemiology is the science of understanding disease in populations. The focus is on the population, underpinned by principles and utilising methods that seek to allow us to generate solid conclusions from apparently uncontrolled situations. In this paper, we argue for the inclusion of epidemiological principles and methods as an additional tool for herd problem-solving, and outline an investigative framework, with examples, to effectively incorporate these principles and methods with other diagnostic approaches during herd problem-solving. Relevant measures of performance are identified, and measures of case frequencies are calculated and compared across time, in space and among animal groupings, to identify patterns, clues and plausible hypotheses, consistent with potential biological processes. With this knowledge, the subsequent investigation (relevant on-farm activities, diagnostic testing and other examinations) can be focused, and actions prioritised (specifically, those actions that are likely to make the greatest difference in addressing the problem if enacted). In our experience, this investigative framework is an effective teaching tool, facilitating epidemiological thinking among students during herd problem-solving. It is a generic and robust process, suited to many herd-based problems.

The creation and evaluation of a model to simulate the probability of conception in seasonal-calving pasture-based dairy heifers.

BACKGROUND: Herd fertility in pasture-based dairy farms is a key driver of farm economics. Models for predicting nulliparous reproductive outcomes are rare, but age, genetics, weight, and BCS have been identified as factors influencing heifer conception. The aim of this study was to create a simulation model of heifer conception to service with thorough evaluation. METHODS: Artificial Insemination service records from two research herds and ten commercial herds were provided to build and evaluate the models. All were managed as spring-calving pasture-based systems. The factors studied were related to age, genetics, and time of service. The data were split into training and testing sets and bootstrapping was used to train the models. Logistic regression (with and without random effects) and generalised additive modelling were selected as the model-building techniques. Two types of evaluation were used to test the predictive ability of the models: discrimination and calibration. Discrimination, which includes sensitivity, specificity, accuracy and ROC analysis, measures a model's ability to distinguish between positive and negative outcomes. Calibration measures the accuracy of the predicted probabilities with the Hosmer-Lemeshow goodness-of-fit, calibration plot and calibration error. RESULTS: After data cleaning and the removal of services with missing values, 1396 services remained to train the models and 597 were left for testing. Age, breed, genetic predicted transmitting ability for calving interval, month and year were significant in the multivariate models. The regression models also included an interaction between age and month. Year within herd was a random effect in the mixed regression model. Overall prediction accuracy was between 77.1% and 78.9%. All three models had very high sensitivity, but low specificity. The two regression models were very well-calibrated. The mean absolute calibration errors were all below 4%. CONCLUSION: Because the models were not adept at identifying unsuccessful services, they are not suggested for use in predicting the outcome of individual heifer services. Instead, they are useful for the comparison of services with different covariate values or as sub-models in whole-farm simulations. The mixed regression model was identified as the best model for prediction, as the random effects can be ignored and the other variables can be easily obtained or simulated.

The effect of paratuberculosis on milk yield--A systematic review and meta-analysis.

Bovine paratuberculosis is a disease characterized by chronic granulomatous enteritis causing protein-losing enteropathy. Adverse effects on animal productivity are key drivers in the attempt to control paratuberculosis at the farm level. Economic models require an accurate estimation of the production effects associated with paratuberculosis. The aim of this study was to conduct a systematic review and meta-analysis to investigate the effect of paratuberculosis on milk production. A total of 20 effect estimates from 15 studies were included in the final meta-analysis. Substantial between-study heterogeneity was observed. Subgroup analysis by case definition and study design was carried out to investigate heterogeneity. The majority of between-study variation was attributed to studies that defined cases on serology. Calculation of a pooled effect estimate was only appropriate for studies that defined cases by organism detection. A reduction in milk yield, corrected for lactation number and herd of origin of 1.87 kg/d, equivalent to 5.9% of yield, was associated with fecal culture or PCR positivity in individual cows.

Profiling oral and digital lesions in sheep in Ireland.

BACKGROUND: During the FMD outbreak in Ireland and the UK in 2001, there was significant uncertainty amongstveterinary practitioners and government veterinary inspectors surrounding the clinical diagnosis of FMD insheep. This situation was complicated by reports of idiopathic oral ulcers that closely resembled FMD ongross appearance which at that time were referred to as ovine mouth and gum obscure disease. METHODS: A field and abattoir study was carried out to determine the frequency, appearance and significance of oraland digital lesions in sheep in Ireland. A total of 3, 263 sheep were examined in 22 flocks, including 1, 969lambs and 1, 294 adults. A further 2,403 animals were examined by abattoir inspections. Animals bearing lesions of interest were identified, samples of the lesions were taken and subsequently examined by bacteriology, electron microscopy, serology, immunohistochemistry and histopathology. RESULTS: Forty four oral and 20 digital lesions were identified and characterised. Oral lesions were recorded mostfrequently in lambs, where the most common cause was orf virus infection. The majority of the oral lesions recorded in the adults was idiopathic and consistent with a diagnosis of idiopathic oral ulceration. A variety of digital lesions was observed, consistent with scald, foot-rot and contagious ovine digital dermatitis (CODD). All of the animals with lesions were seronegative to FMD virus (FMDV). CONCLUSIONS: There was no difficulty in differentiating these lesions from those caused by FMDV on the basis of flockhistory and careful clinical examination.

The effect of Lameness before and during the breeding season on fertility in 10 pasture-based Irish dairy herds.

BACKGROUND: The effects of lameness on fertility have been documented frequently but few data are available from seasonally breeding, pasture-based herds (such as those used in Ireland) where cows are housed during the winter months but managed at pasture for the remainder of the year. This study determined the prevalence of lameness in a group of 786 cows in 10 pasture-based Irish dairy herds before, during and after the breeding season and assessed the relationship between lameness and the reproductive performance in these herds through serial locomotion scoring during the grazing period. RESULTS: Lameness prevalences of 11.6 % before, 14.6 % during and 11.6 % after the breeding season were found and these compared favourably to results from housed cattle and are similar to other studies carried out in grazing herds. A Cox proportional hazards model with locomotion score as time varying covariate was used. After controlling for the effect of farm, month of calving, body condition score at calving, body condition score loss after calving and economic breeding index, cows identified as lame during the study were less likely to become pregnant. Cows lame before the earliest serve date but no longer lame during the breeding season, cows becoming lame after the earliest serve date and cows identified lame both before and after this date were respectively 12 %, 35 % and 38 % less likely to become pregnant compared to cows never observed lame during the study. However, these findings were only significant for cows becoming lame after the earliest serve date and cows lame both before and after the start of breeding. CONCLUSIONS: This study found that the reproductive efficiency was significantly (p < 0.05) lower in cows becoming lame during the breeding season and cows lame before and during the breeding season compared to non-lame cows. Cows no longer lame during the breeding season had a lower Submission Rate to first serve within 3 weeks of earliest serve date. However, the Pregnancy Rate was not significantly (p > 0.05) lower in these animals compared to cows never diagnosed as lame. In addition to lameness status, nutritional status and genetics were found to influence the reproductive performance in pasture-based Irish dairy herds.

Bovine congenital erythropoietic protoporphyria in a crossbred limousin heifer in Ireland.

An unusual case of an 11-month-old, black Limousin-cross heifer, with an 8-month history of episodic seizures and photosensitisation, was referred by a veterinary practitioner to the Farm Animal Section of the UCD Veterinary Hospital, School of Veterinary Medicine, University College Dublin, Ireland, in August 2014. Following an investigation, a diagnosis of Bovine Congenital Erythropoietic Protoporphyria (BCEPP) was made. To the authors' knowledge this is the first report of such a case in Ireland. BCEPP should be considered as a differential diagnosis in young animals displaying periodic seizures and/or photosensitisation.

Nematode control in suckler beef cattle over their first two grazing seasons using a targeted selective treatment approach.

BACKGROUND: With concerns over the development of anthelmintic resistance in cattle nematode populations, we must re-examine our approach to nematode control in cattle. Targeted selective treatments (TST), whereby individual animals are treated instead of entire groups, are being investigated as an alternative. The study objective was to determine if anthelmintic usage could be reduced using a TST-based approach to nematode control in spring-born suckler beef cattle over their first and second grazing seasons (SGS) without affecting performance. In the first grazing season (FGS), 99 calves with an initial mean (s.d.) calf age and live weight on day 0 (June 28(th) 2012) of 107 (23.1) days and 160 (32.5) kg, respectively, were used. The study commenced on day 0 when calves were randomised and allocated to one of two treatments; 1), standard treatment (control) and 2), TST. Control calves were treated subcutaneously with ivermectin on days 0, 41 and 82 in the FGS. All calves were treated with ivermectin on day 124 and housed on day 133. In the SGS, only heifer calves from the FGS were used and control heifers were treated with ivermectin on day 393. Animals were weighed, blood and faecal sampled every three weeks. The TST animals were treated with ivermectin if thresholds based on a combination of plasma pepsinogen concentrations, faecal egg count and/or the presence of Dictyocaulus viviparus larvae in faeces (FGS only) were reached. RESULTS: No TST calves reached the treatment threshold criteria in the FGS. The FGS average daily live weight gain (ADG ± s.e.m.) for control and TST group calves was 0.89 ± 0.02 kg and 0.94 ± 0.02 kg day(-1), respectively (P = 0.17). In the SGS, all heifers were treated with ivermectin on day 431 due to clinical signs of respiratory disease. The ADG for control and TST heifers from turnout on day 321 to day 431 was 0.90 ± 0.04 and 0.80 ± 0.04 kg day(-1), respectively (P = 0.03). CONCLUSIONS: Spring-born FGS suckler beef calves require minimal anthelmintic treatment to maintain performance. In contrast, clinical parasitic disease may develop in the SGS unless appropriate anthelmintic treatment is provided.

Disease screening profiles and colostrum management practices on 16 Irish suckler beef farms.

BACKGROUND: Calf output is a key element in determining the profitability of a suckler beef enterprise. Infectious agents such as Bovine Virus Diarrhoea (BVD) virus, colostrum management and parasitic challenge can all affect calf output. Prior to the national BVD eradication programme, there was little published information on either the prevalence or effect of BVD in Irish beef herds. There is little published information on colostrum management practices in Irish commercial beef herds and there have also been few studies published on the prevalence of liver fluke or rumen fluke infection in Irish beef herds. Sixteen farms participating in the Teagasc/Farmers Journal BETTER farm beef programme were used in this study. Fourteen herds were screened for the presence of BVD virus in 2010 using RT-PCR. In 13 herds, blood samples were collected from calves (2-14 days of age) in November 2011 - April 2012 to determine their passive immune status using the zinc sulphate turbidity (ZST) test, while in 12 herds, blood and faecal samples were taken in order to determine the level of exposure to gastrointestinal and hepatic helminths. RESULTS: The overall prevalence of BVD virus-positive cattle was 0.98% (range 0 - 3% per herd, range 0.6 - 3.0% per positive herd). Eighteen of the 82 calves (22%) sampled had ZST values less than 20 units (herd mean range 17.0 - 38.5 units) indicating a failure of passive transfer. The overall animal-level (herd-level) prevalence of liver fluke and rumen fluke infection in these herds was 40.5% (100%) and 20.8% (75%), respectively. CONCLUSIONS: The potential costs associated with the presence of animals persistently infected with BVD virus through the increased use of antibiotics; the rate of failure of passive transfer of colostral immunoglobulins and the high prevalence of liver fluke infection in these herds highlight that some Irish suckler beef farms may not be realizing their economic potential due to a range of herd health issues. The use of farm-specific herd health plans should be further encouraged on Irish suckler beef farms.

Aspects of bovine herpesvirus 1 and bovine viral diarrhoea virus herd-level seroprevalence and vaccination in dairy and beef herds in Northern Ireland.

BACKGROUND: Infections with bovine herpesvirus 1 (BoHV-1) and bovine viral diarrhoea (BVD) virus cause diseases of cattle with a worldwide distribution. The primary objective of the present study was to describe aspects of herd-level BoHV-1 and BVDV seroprevalence (based on testing of pooled sera) and control on farms in Northern Ireland, including vaccine usage. An indirect antibody ELISA test (SVANOVA, Biotech AB, Uppsala, Sweden) was applied to serum pools which were constructed from serum samples taken for a cross-sectional study of a convenience sample of 500 Northern Irish dairy and beef cow herds in 2010, for which vaccination status was determined by telephone survey. The herd-level seroprevalence of BoHV-1 and BVDV in Northern Ireland was estimated in non-vaccinating herds and associations between possible risk factors (herd type and herd size (quartiles)) and herd-level prevalence were determined using chi-squared analysis. RESULTS: The herd-level seroprevalence (of BoHV-1 and BVDV) in non-vaccinating herds was 77.3% (95% CI: 73.6-80.9%) and 98.4% (95% CI: 97.3-99.5%) respectively in the cross-sectional study. A significant difference existed in BoHV-1 herd-level seroprevalence between dairy and beef herds (74.7% vs 86.5% respectively; p < 0.02) though not for BVDV seroprevalence (98.5% vs 98.3% respectively; p > 0.91). A significant association was found between herd size (quartiles) and herd-level classification for BoHV-1 herd-level seroprevalence based on cut-off percentage positivity (COPP) (p < 0.01) while no such association was found for BVDV (p = 0.22). 15.5% and 23.8% of farmers used BoHV-1 and BVDV vaccines, respectively. BoHV-1 vaccine was used in 30% of dairy herds and in 11% of beef herds, while BVDV vaccine was used in 46% and 16% of dairy and beef herds, respectively. CONCLUSIONS: The results from this study indicate that the true herd-level seroprevalences to bovine herpesvirus 1 and bovine virus diarrhoea virus in non-vaccinating herds in Northern Northern Ireland are 77.3% (95% CI: 73.6-80.9%) and 98.4% (95% CI: 97.3-99.5%), respectively. The present study will assist in guiding regional policy development and establish a baseline against which the progress of current and future control and eradication programmes can be measured.

Bulk milk ELISA and the diagnosis of parasite infections in dairy herds: a review.

The bulk milk enzyme-linked immune sorbent assay (ELISA) is a rapid and inexpensive method of assessing herd exposure to pathogens that is increasingly being used for the diagnosis of parasite infections in dairy herds. In this paper, with the dairy herd health veterinarian in mind, we review the principles of the assay and the recent literature on the potential role of bulk milk ELISA for the diagnosis of ostertagiosis, fasciolosis, parasitic bronchitis due to cattle lung worm and neosporosis. It is generally accepted that assay results reflect exposure to the parasite rather than the presence of active infection. Bulk milk ELISA can be a useful tool for the veterinary practitioner as a component of a herd health monitoring programme or in the context of a herd health investigation. It can also play a role in regional or national surveillance programmes. However, the results need to be interpreted within the context of the herd-specific health management, the milk production pattern and the parasite life cycle.

Herd health status and management practices on 16 Irish suckler beef farms.

BACKGROUND: There have been few studies published internationally which document herd health management practices in suckler beef herds and no published Irish studies. The study objective was to document herd health status and management practices on sixteen Irish suckler beef herds over a two year period (2009-2010). The farms used in the study were part of the Teagasc BETTER farm beef programme. The mean (s.d.) herd size, stocking rate and farm size was 68 cows (27.6), 2.0 LU/ha (0.3) and 64.3 (21.6) adjusted hectares, respectively. Two questionnaires were designed; 1) a farmer questionnaire to collect information on farm background and current herd health control practices and 2) a veterinary questionnaire to collect information on the extent of animal health advice given by veterinarians to their clients and identification of any on-farm herd health issues. RESULTS: Dystocia, calf pneumonia, and calf diarrhoea, in that order, were identified as the primary herd health issues in these Irish suckler beef herds. In addition, substantial deficiencies in biosecurity practices were also identified on these farms. CONCLUSIONS: The findings of this study may serve as the focus for future research in animal health management practices in Irish suckler beef herds.

The postpartum endometrial inflammatory response: a normal physiological event with potential implications for bovine fertility.

After calving, the bovine endometrium undergoes marked morphological and functional changes that are necessary for subsequent re-breeding. Regulation and integration of these key events are largely uncharacterised. Here, endometrial swabs and biopsies were taken at 15, 30 and 60 days postpartum (DPP) from 13 healthy primiparous cows, 10 of which subsequently conceived, with a view to characterising innate and inflammatory gene expression profiles. Endometrial biopsies exhibited severe inflammation (>75 leukocytes per high-power field) at 15 DPP, which had begun to resolve by 30 DPP and had completely resolved by 60 DPP. The severe inflammation at 15 DPP coincided with uterine infection in all cows and a significant increase (P < 0.05) in the expression of all of 16 genes investigated, including CD45, IL8, IL6, IL1, TNF, TAP, SAA3 and HP at 15 DPP, relative to 60 DPP. All of these parameters had begun to return to normal physiological levels at 30 DPP. Systemically, serum protein concentrations of IL-8 were elevated at 15 DPP compared with 60 DPP (78 pgmL(-1)vs 48 pgmL(-1); P = 0.02). These results indicate that endometrial inflammation, leukocyte infiltration and increased expression of pro-inflammatory, antimicrobial and acute-phase protein genes are expected features of the postpartum period, critical to bacterial clearance and uterine involution.

Histopathological and molecular evaluation of Holstein-Friesian cows postpartum: toward an improved understanding of uterine innate immunity.

Bovine uterine disease reduces milk yield, impairs fertility and has implications for animal welfare. During involution, the uterus is usually exposed to multiple potential bacterial pathogens which are cleared by successful orchestration of the local inflammatory response. Unsuccessful resolution leads to the development of disease. The aim of this study was to characterize the local innate immune response in the uterus during physiological involution using histopathological and molecular analyses in 9 cows, 2 weeks after calving (early postpartum, EPP), and 4 cows, 9 weeks after calving (late postpartum, LPP). Uterine biopsies taken from each cow were classified by histopathology, and RNA was extracted for molecular analysis. Two EPP cows were classified with a mild, 5 with a moderate and 2 with a severe inflammatory response. Relative gene expression analysis was then performed using quantitative real-time PCR (qRT-PCR) and specific primers for genes encoding Toll-like receptors (TLRs), chemokines, cytokines, acute phase proteins (APPs) and antimicrobial peptides (AMPs). TLR4, transcription factor NFKB1 and the inflammatory cytokines IFNG, IL1A, IL6, IL8, IL12A were all significantly increased in EPP cows (P<0.05). Increase in HP, SAA3, TAP and DEFB5 genes was particularly marked in cows with severe inflammation. These results reveal evidence of an inflammatory uterine environment in the early postpartum period with significant induction of both AMP and APP genes. Histopathological grades in EPP cows are underpinned by quantitative changes in gene expression. Understanding the molecular mechanisms contributing to uterine immunity in the early postpartum period may identify candidate genes associated with the resolution of inflammation.

Routine Herd Health Data as Cow-Based Risk Factors Associated with Lameness in Pasture-Based, Spring Calving Irish Dairy Cows.

Herd-level risk factors related to the cow's environment have been associated with lameness. Uncomfortable stall surface and inadequate depth of bedding as well as abrasive alley way surface are contributing factors to increased levels of lameness. Access to pasture has been found as having a beneficial effect on cows' locomotion. However, dairy cattle managed under grazing conditions are exposed to a different set of risk factors for lameness, mainly associated with cow tracks. Cow-based risk factors for lameness are not as clearly defined as the herd level risk factors. The objective of the present study was to use routine herd health monitoring data to identify cow-based risk factors for lameness and utilise this information to indicate cows at risk of developing lameness in the first 150 days of lactation. Lameness data were gathered from 10 pasture-based dairy herds. A total of 1715 cows were monitored, of which 1675 cows were available for analysis. Associations between lameness status and potential cow-level risk factors were determined using multivariable logistic regression. Parity 3 and 4 + cows showed odd ratios (OR's) for lameness of 3.92 and 8.60 respectively (95% confidence interval (CI) 2.46-6.24; 5.68-13.0). Maximum loss of Body condition score (BCS) after calving exhibits OR's for lameness of 1.49 (95% CI 1.08-2.04) if cows lost 0.5 in BCS after calving and 2.26 (95% CI 1.30-3.95) for cows losing more than 0.5 BCS. Animals calving in BCS 3.25 and ≥ 3.5 had correlating OR's of 0.54 (95% CI 0.34-0.87) and 0.33 (95% CI 0.16-0.65) for being lame compared to cows calving with BCS ≤ 2.75. Data gathered as part of herd health monitoring can be used in conjunction with lameness records to identify shortcomings in lameness management. Findings and recommendations on lameness management can be formulated from readily available information on cow-based risk factors for lameness.