Lesions found at foot trimming of dairy goats: Baseline data for comparing lesions and locomotion scoring.

Data on the foot lesions of housed dairy goats, especially those that are not lame, is sparse. In this study, visits were made to four farms for whole herd locomotion scoring after milking and to observe routine foot trimming. During trimming, the amount of trimming required for each hoof was recorded, alongside the presence of lesions. The process was repeated at the next routine foot trim on three of the four farms (on Farm 1 whole herd locomotion scoring after milking was not feasible). Across both visits, 3445 locomotion scores were recorded, alongside 3850 trimming and lesion records. There were large differences between farms and visits in the proportion of lame goats (6.7 to 25.5%) and in the proportion of goats which needed a substantial trim of all four feet (15.1-33.1%). Hoof lesions were observed in 65.5% of trimmed goats. We defined lesions by their site and presence of separation and/or granuloma, with white line separation being the most commonly recorded lesion (41.5% of goats). On all visits on the three farms which were locomotion scored, the number of goats recorded as lame was lower than the number observed with white line lesions, but the relative proportion ranged from 17% to 95.4%. Separations were much more common than granulomas, as granulomas were usually accompanied by separation. Toe lesions were much more likely to be associated with granulomas than white line lesions, with 91.5% of toe separations having granulomas but only 10.6% of white line separations. This study provides useful baseline data for comparing lesions and locomotion scoring between goat herds but also identifies areas where we need more data and more consensus.

Effects of climate and farm management practices on bovine digital dermatitis in spring-calving pasture-based dairy farms in Taranaki, New Zealand.

To investigate the effect of climate and farm management practices on prevalence of bovine digital dermatitis (BDD) in spring-calving farms in Taranaki, New Zealand, whole herd assessments of BDD were made on 57 farms which had been previously identified as having cows with BDD. Assessments of BDD lesions were made on five occasions between early lactation (September 2015) and drying-off (May 2016; at approximately 6-week intervals). Along with the clinical assessment, data on farm management practices were collected using questionnaires. In addition, climate data including rainfall and soil/air temperature were obtained from a local weather station. The raw temporal pattern was analysed using a generalised estimating equation method, followed by a mixed effects negative binomial model which modelled the associations between prevalence and the covariates including management practices, rainfall and soil temperature. The highest farm and cow level prevalences were seen on the second visit (27/Oct/2015-11/Dec/2015) and were lowest on the fourth visit (29/Jan/2016-10/Mar/2016). Farms with a higher prevalence at the first visit tended to have a higher prevalence at later visits, even though the affected individuals were often different. There was thus a strong correlation (0.94) between prevalence (proportion of cows affected at each time point) and incidence (proportion of cows with new affections at each time point). Two climate measurements were found to have associations with BDD prevalence. Firstly, increased rainfall in the previous month was associated with decreased cow level prevalence; secondly, there was a quadratic relationship between prevalence and soil temperature, with prevalence increasing as soil temperature increased from 11.8 °C to approximately 18 °C and then decreasing as soil temperature increased from approximately 18 °C to 23.9 °C. In addition to the effect of climate, using outside staff to perform hoof trimming was found to increase the risk of BDD affection (risk ratio [RR]: 2.06, 95% confidence interval [CI]: 1.05-4.06).

Farm level risk factors for bovine digital dermatitis in Taranaki, New Zealand: An analysis using a Bayesian hurdle model.

As part of a cross-sectional study of bovine digital dermatitis (BDD) in 60,455 cows across 224 herds, in Taranaki, a region of the North Island of New Zealand, from September 2014 to February 2015, questionnaires from 114 farms were analysed to identify the key management practices which affect the probability of a farm being affected by BDD and the prevalence of an individual cow being affected on affected farms. The data from the questionnaires were analysed using a Bayesian hurdle model. Two factors were identified as being associated with farm level infection status: (1) milking parlour type; farms which had rotary platforms were more likely to be recorded as having BDD than those which had herringbone parlours (odds ratio, OR, 3.19; 95% probability interval, PI, 1.31-8.51); and (2) young stock movement; farms whose young stock were reared on farms alongside heifers from other farms had a higher odds of being BDD positive than farms where heifers were kept separate (OR 4.15; 95% PI 1.39-15.27). Two factors were associated with an increase in the prevalence of BDD within affected farms: (1) farms which used outside staff to trim feet had a higher prevalence of BDD (prevalence ratio, PR, 3.13; 95% PI 1.25-7.29) than farms which did not use outside staff; and (2) farms examined in spring (September to November) had a higher prevalence of BDD (PR 2.16; 95% PI 1.05-4.43) than farms examined in summer (December to February).

Estimating the true prevalence of bovine digital dermatitis in taranaki, New Zealand using a bayesian latent class model.

A Bayesian latent class model was developed to estimate the true prevalence of bovine digital dermatitis (BDD) in Taranaki, New Zealand. This model allowed farms to have zero prevalence as well as also accounting for between farm heterogeneity that was conditional on whether a farm was positive for bovine digital dermatitis. The estimated true farm level prevalence was 68.9% (95% credible interval [CrI]: 50.0%-85.7%), while on infected farms the overall cow level prevalence (number of infected cows/total number of cows on infected farms) was 2.9% (95%CrI: 2.1%-4.3%). The sensitivity analyses suggested that the prevalence estimates were reasonably robust when the variation of the priors fell within the biologically plausible range. These results indicated that visual inspection of standing animals during milking was sufficiently accurate to identify infected farms. However, for every 100 animals identified through visual inspection, 84 animals with lesions were missed. In other words, 46% (calculated as 84/184) of true positives at the animal level could be missed by visual inspection. The high and robust specificity (99.9%, 95%CrI: 99.8%-99.9%) suggested that lesions reported as BDD were very unlikely to be false positives.

Farm and cow-level prevalence of bovine digital dermatitis on dairy farms in Taranaki, New Zealand.

AIMS: The aims of this cross-sectional study were to investigate the herd and cow-level prevalence of bovine digital dermatitis (BDD) in dairy farms in the northern Taranaki region of New Zealand, and to identify whether there was any spatial clustering of herds with the disease. METHODS: A survey of 224 dairy farms in the northern Taranaki region of New Zealand was undertaken from September 2014 to February 2015. Following training in robust criteria to confirm BDD visually, a technician inspected the rear feet of every milking cow on the farms during milking. The identity of cows with lesions and the feet involved were recorded. The proportion of cows affected among the inspected population (cow-level prevalence), the proportion of a herd affected (farm-level prevalence), and proportion of farms with ≥1 cow with lesions, were calculated. A bivariate K function analysis was then used to assess whether farms with ≥1 cow with lesions were clustered, after accounting for the distribution of the farms involved in the study. RESULTS: Bovine digital dermatitis lesions were observed on 143/224 (63.8 (95% CI=57.5-70.1)%) farms. Within-farm prevalence was 0% on 81 (36.2%) farms, between >0 and <3% on 120 (53.5%) farms, with a maximum prevalence of 12.7% on one farm. Overall, cow-level prevalence was 707/60,455 (1.2 (95% CI=0.9-3.0)%), and on affected farms was 707/41,116 (1.7 (95% CI=1.4-2.1)%). In affected cows, 268/707 (37.9%) had a lesion on left foot only, 262/707 (37.1%) on the right foot only and 177/707 (25.0%) on both feet. The K function analysis showed no evidence of clustering of farms with BDD. CONCLUSIONS: Bovine digital dermatitis was widespread among the survey farms, but there was no evidence that there was any clustering of herds with BDD. The cow-level prevalence on affected farms was much lower than reported elsewhere. CLINICAL RELEVANCE: Although the prevalence at the cow level was low, if these data are representative of other regions of New Zealand, BDD could easily become a major problem on dairy farms in New Zealand, as has been observed in other countries.

Further investigation of lameness in cows at pasture: an analysis of the lesions found in, and some possible risk factors associated with, lame New Zealand dairy cattle requiring veterinary treatment.

Previous descriptive analysis of data collected from veterinary visits to lame cows in the Taranaki region of New Zealand between December 1995 and July 2007 showed an association between both breed and age and lesion type and site. However, that simple analysis had significant limitations as it did not take account of more than 2 factors at the same time and did not evaluate the effect of time (either year or season). This analysis was designed to overcome those limitations. First, correspondence analysis, a multivariate method of analysis, was used to simultaneously evaluate the relationship between the 3 most commonly recorded causes of lameness (i.e., white line disease, sole injury, and axial disease, all of which are diseases of the claw horn), and 4 groups of predictor variables: foot (front or hind), breed (Jersey or Friesian), age (heifer or cow), and claw (lateral or medial). Second, time series analysis was used to ascertain the effect of season on lesion type and identify the change over years in proportional morbidity. The correspondence analysis clearly separated the 3 diseases, showing that differences between these 3 diseases in their risk factors and their etiology. Each disease clustered with a group of predictor variables. White line disease was linked to lateral claw, hind foot, cow, and Friesian breed; sole injury was linked to heifer and medial claw; and axial disease to Jersey and front foot. As sole injury and axial disease are diseases that occur principally in cows at pasture, this is the first full analysis of risk factors for those diseases. The time series analysis further strengthened the conclusion that these 3 diseases have different risk factors, as, even in the strongly seasonal New Zealand system, significant differences in seasonality occurred between them. This analysis adds further to the data which show that claw horn diseases have different etiologies and need to be treated separately for both research purposes and for lameness management on-farm. This analysis is only a starting point; more research is required, particularly longitudinal studies, to better understand the differences in etiology between the main causes of lameness due to claw horn disease, especially in cows kept at pasture, so that we can better target prevention.

A descriptive analysis of the foot lesions identified during veterinary treatment for lameness on dairy farms in north Taranaki.

AIM: To analyse the records made during routine veterinary treatment of lame cows, to identify the types of lesions causing lameness of dairy cows in north Taranaki, their relative prevalence and distribution, and some of the cow-associated factors which affect these parameters. METHODS: Data concerning cow age and breed, lesion type, lesion site, and whether the examination was a revisit were collected from records of veterinary visits between December 1995 and July 2007. Data were analysed on a single- or two-factor basis, using chi(2) and, where suitable, calculation of OR. RESULTS: The total number of individual cow treatments recorded was 4,488. The most commonly recorded lesion was white-line disease (WLD) (42% of diagnoses at first examination), and the second was sole injury (29%). Heifers accounted for 19% of cases, similar to the expected replacement rate. Jerseys accounted for 18% of cases, lower than the proportion of purebred Jerseys in the region (27%). There was a significant effect of age and breed on the prevalence and distribution of lesions. There were also significant differences between lesion types in their location, which were also influenced by breed and age. CONCLUSIONS: This study provided a comprehensive overview of the lesions causing lameness in dairy cattle in north Taranaki, and identified some of the factors which influence the development of lesions. More research is needed to better establish the aetiology and pathogenesis of lameness in cattle under New Zealand conditions. CLINICAL RELEVANCE: This study provides baseline data with which veterinarians can compare their results to identify significant patterns on specific farms, which will suggest specific causal factors for lameness on those farms and thus better guide prevention programmes.

Behavioural characteristics of dairy cows with lameness in Taranaki, New Zealand.

AIM: To investigate possible relationships between the incidence of lameness in dairy cows, and walking order from the paddock into the milking shed, milking order, and dominance structure in the herd. METHODS: Ten dairy herds from the Taranaki region in New Zealand, with an average herd size of 183 cows, were observed during early, mid and late lactation. Each observation period consisted of five observations within 1 week, totalling 15 observations per farm. Three observers recorded the daily movement of cows between paddocks and the milking shed at each of three different locations. Additionally, the dominance structure of 21 cows per herd, randomly selected at the beginning of the study, was determined at the beginning of each of the three observation periods, on the basis of antagonistic behaviour. RESULTS: Within herds, walking and milking order showed a Kappa value of 0.31, reflecting fair agreement beyond chance. Based on the multivariate model, an increased risk of lameness was found for cows that walked or were milked in the last quarter of the herd (OR=1.8 and 1.5, respectively) compared with animals that walked/were milked in the first three quarters of the herd. The dominance structure of the randomly selected animals remained stable during the course of the lactation. High dominance animals tended to walk at the front of the herd and get milked first, whereas low dominance animals tended to walk at the back of the herd and get milked last. Although lameness was not significantly related to the dominance group, this could have been due to the low power of the study. CONCLUSIONS: The results of the study suggested that there is a relationship between the position of the animal in the herd and the risk of lameness in dairy cows, but that the strength of this relationship varied between herds. CLINICAL RELEVANCE: Walking/milking order was a risk factor for conditions causing lameness in dairy cows, and for the effective management of herd lameness problems it is important for farmers to be aware of this relationship.

Environmental and behavioural factors affecting the prevalence of foot lameness in New Zealand dairy herds - a case-control study.

A case-control study of environmental and behavioural factors influencing foot lameness was undertaken on 62 dairy herds comprising an average of 185 milking cows in Taranaki, New Zealand. Thirty two case herds were identified as having had at least 10 per cent of the cows lame during the milking season in which the herd was studied, and thirty control herds were selected on the basis that no more than 3 per cent of cows in these herds had been lame per year for at least two years immediately prior to investigation. Each herd was visited at both a morning and an afternoon milking, and 58 risk factors were measured between the time the farmer began to assemble the cows for milking and the completion of milking. Comparison of single variables between case and control herds identified 24 which showed differences (p<0.10). These variables were then subjected to stepwise multivariate logistic regression, and statistically significant variables in this analysis were used to create a tentative path diagram of possible causal web relationships between the various risk factors and the outcome variable, the lameness prevalence level. Information from a review of the published literature was used to include further variables to the 24 into the initial (or null hypothesis) path model. Logistic path analysis was then used to eliminate non-significant paths from the diagram, leaving 19 arrows joining 13 variables in the final path diagram, compared with 33 joining 20 variables in the initial version. The most influential variables in explaining variation between case and control herds were the average level of maintenance of the track and the degree of patience shown by the farmer in bringing the cows in for milking. Overall, factors associated with the movement of animals to the milking shed explained 40 per cent of the variation (deviance) with regard to the lameness prevalence level. Risk factors associated with characteristics of the milking process explain 24 per cent, and risk factors associated with characteristics of the cows in the herd explain 9.5 per cent. Recommendations are made on management changes which deserve further investigation as ways of reducing lameness problems in dairy herds.