Development and evaluation of predictive models for pregnancy risk in UK dairy cows.

One suggested approach to improve the reproductive performance of dairy herds is through the targeted management of subgroups of biologically similar animals, such as those with similar probabilities of becoming pregnant, termed pregnancy risk. We aimed to use readily available farm data to develop predictive models of pregnancy risk in dairy cows. Data from a convenience sample of 108 dairy herds in the UK were collated and each herd was randomly allocated, at a ratio of 80:20, to either training or testing data sets. Following data cleaning, there were a total of 78 herds in the training data set and 20 herds in the testing data set. Data were further split by parity into nulliparous, primiparous, and multiparous subsets. An XGBoost model was trained to predict the insemination outcome in each parity subset, with predictors from farm records of breeding, calving and milk recording. Training data comprised 74,511 inseminations in 45,909 nulliparous animals, 86,420 inseminations in 39,439 primiparous animals, and 158,294 inseminations in 32,520 multiparous animals. The final models were evaluated by predicting with the testing data, comprising 31,740 inseminations in 19,647 nulliparous animals, 38,588 inseminations in 16,215 primiparous animals, and 65,049 inseminations in 12,439 multiparous animals. Model discrimination was assessed by calculating the area under receiver operating characteristic curves (AUC); model calibration was assessed by plotting calibration curves and compared across test herds by calculating the expected calibration error (ECE) in each test herd. The models were unable to discriminate between insemination outcomes with high accuracy, with an AUC of 0.63, 0.59 and 0.62 in the nulliparous, primiparous and multiparous subsets, respectively. The models were generally well-calibrated, meaning the model-predicted pregnancy risks were similar to the observed pregnancy risks. The mean (SD) ECE in the test herds was 0.038 (0.023), 0.028 (0.012) and 0.020 (0.008) in the nulliparous, primiparous and multiparous subsets respectively. The predictive models reported here could theoretically be used to identify subgroups of animals with similar pregnancy risk to facilitate targeted reproductive management; or provide information about cows' relative pregnancy risk compared with the herd average, which may support on-farm decision-making. Further research is needed to evaluate the generalizability of these predictive models and understand the source of variation in ECE between herds; however, this study demonstrates that it is possible to accurately predict pregnancy risk in dairy cows using readily available farm data.

Using Object-Oriented Simulation to Assess the Impact of the Frequency and Accuracy of Mobility Scoring on the Estimation of Epidemiological Parameters for Lameness in Dairy Herds.

Mobility scoring data can be used to estimate the prevalence, incidence, and duration of lameness in dairy herds. Mobility scoring is often performed infrequently with variable sensitivity, but how this impacts the estimation of lameness parameters is largely unknown. We developed a simulation model to investigate the impact of the frequency and accuracy of mobility scoring on the estimation of lameness parameters for different herd scenarios. Herds with a varying prevalence (10, 30, or 50%) and duration (distributed around median days 18, 36, 54, 72, or 108) of lameness were simulated at daily time steps for five years. The lameness parameters investigated were prevalence, duration, new case rate, time to first lameness, and probability of remaining sound in the first year. True parameters were calculated from daily data and compared to those calculated when replicating different frequencies (weekly, two-weekly, monthly, quarterly), sensitivities (60-100%), and specificities (95-100%) of mobility scoring. Our results showed that over-estimation of incidence and under-estimation of duration can occur when the sensitivity and specificity of mobility scoring are <100%. This effect increases with more frequent scoring. Lameness prevalence was the only parameter that could be estimated with reasonable accuracy when simulating quarterly mobility scoring. These findings can help inform mobility scoring practices and the interpretation of mobility scoring data.

An Observational Study Investigating Potential Risk Factors and Economic Impact for Bovine Ischaemic Teat Necrosis on Dairy Farms in Great Britain.

Bovine ischaemic teat necrosis (ITN) is an emerging disease of unknown aetiology that affects the teats of dairy cattle. It causes economic and animal welfare issues with many animals being culled. No effective treatments or epidemiological data to inform control strategies are currently available. The aim of this observational study was to investigate farmer-reported experiences and identify potential farm-level risk factors. In January 2018, a questionnaire was sent to a random sample of 1,855 Great Britain (GB) dairy farmers. A usable response rate of 12.3% was obtained. Fifty-one per cent [95% confidence interval (CI): 44.4-57.8%] of farmers reported having experienced ITN on their farm between 1985 and 2018. Rising numbers of farms indicated that ITN is an emerging disease with 46.3% of farmers reporting the first case in the 3 years up to 2018. At the animal level, 47.3% (95% CI: 38.7-55.9%) of the cases occurred during the first lactation and 78.9% (95% CI: 75.2-82.6%) within the first 90 days in milk. Only 20.8% (95% CI: 15.9-26.4%) of the cases were reported to recover, whereas 22.8% (95% CI: 17.8-28.5%) of the cases required culling. The remaining cases experienced complications such as loss of a teat and/or mastitis. From these data, the cost of ITN, through production losses and expenditure, was estimated to be £1,121 per farm per year. The costs were estimated at £720, £860 and £2,133 for recovered, complicated and culled cases, respectively. Univariable and multivariable logistic regression models were used to explore the associations between the presence of ITN on farm and various risk factors. The presence of udder cleft dermatitis (UCD) (odds ratio 2.80; 95% CI: 1.54-5.07; p < 0.01) and chapped teats (odds ratio 6.07; 95% CI: 1.96-18.76; p < 0.01) in the milking herd was associated with the presence of ITN at the farm level. This is the first national questionnaire of ITN within GB and highlights the association of UCD and chapped teats with ITN at the farm level. While there are many limitations and potential bias around farmer questionnaires, these findings highlight several key areas for further disease investigation and possible intervention.

Clinical and Pathological Features of Bovine Ischaemic Teat Necrosis.

Bovine ischaemic teat necrosis (ITN) is an emerging disease of unknown aetiology affecting mostly dairy cows in the early stages of first lactation and a substantial welfare concern frequently leading to premature culling and economic losses. Specific diagnostic criteria are lacking. The aims of this study were to develop an appropriate ITN grading system, describe the histopathological changes and investigate the potential aetiological role of several pathogens in 47 cows with 73 ITN lesions from 28 farms. ITN lesions were allocated to one of three broad macroscopic categories: presence of a non-proliferative lesion on the teat (type 1); proliferative teat lesion with crusting (type 2); severe purulent to eosinophilic, ulcerative and necrotising dermatitis and sloughing or total absence of the teat (type 3). Lesions were mostly observed on the medial aspect of the teat but there was no anatomical predisposition as to which teats were more frequently affected. In approximately 50% of the ITN teats reviewed, the lesions were continuous with the skin of the udder and 34.2% of cases had sloughed or partially sloughed teats. The main histological findings were: focally extensive severe purulent to eosinophilic, ulcerative and necrotizing dermatitis; serocellular crust formation; and epidermal hyperplasia with dyskeratosis. Some lesions also had leucocytoclastic to eosinophilic vasculitis and thrombosis with ischaemic necrosis. Macroscopic and histological analyses confirmed the suspected ischaemic nature of the lesions but the specific aetiopathogenesis was elusive with a wide range of bacteria present, probably as opportunistic infections. However, Treponema spp and Orthopox virus were excluded as major aetiological agents. This study establishes a foundation for further investigations of the pathogenesis of bovine ITN and a basis for consistency in diagnosis and classification of the stage of disease. The findings are also key to further understanding disease progression and prognosis.

Assessing the effects of weekly preweaning health scores on dairy calf mortality and productivity parameters: cohort study.

A longitudinal cohort study was conducted to follow the health of 787 calves from one UK dairy farm over a two-and-a-half-year period. Weekly health scores were gathered using a modified version of the Wisconsin Calf Scoring system (which did not record ear position) until calves were eight weeks of age, combined with data on colostral passive transfer, mortality, age at first conception and 305-day milk yield. High morbidity levels were detected, with 87 per cent of calves experiencing at least one clinically significant event (diarrhoea, pyrexia, pneumonia, nasal or ocular discharge, navel ill or joint ill). High rectal temperature, diarrhoea and a cough were the most prevalent findings. The effect of total protein levels was significantly associated with the development of pyrexia as a preweaning calf (P<0.01), but no other clinical health scores. The majority of moribund calves had just one clinically severe clinical sign detected at each of the weekly recordings. The overall mortality rate was 21.5 per cent up to 14 months of age, with 12.7 per cent of calves dying during the preweaning period. However, most calves that died were not recorded as having experienced a severe clinical sign in the time between birth and death, indicating a limitation in weekly calf scoring in detecting acute disease leading to death. Therefore, more frequent calf scoring or use of technology for continuous calf monitoring on farms is required to reduce mortality on farms with high disease incidence rates.