Abstract
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).
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