Sensitivity and specificity of mobility scoring for the detection of foot lesions in pasture-based Irish dairy cows.

Lameness is an important production disease in dairy cows worldwide and has detrimental effects on cows' welfare, production, and reproductive performance, thus affecting the sustainability of dairy farming. Timely and effective detection of lameness allows for effective treatment, minimizing progression of disease, and maximizing the prognosis of recovery. Mobility scoring (MSc) is a 4 point (0-3) visual lameness scoring system that is the industry standard in several countries. However, few studies have examined the sensitivity (Se) and specificity (Sp) of MSc to detect foot lesions. The aim of this observational study was to determine the Se and Sp of MSc to detect foot lesions in dairy cattle in a pasture-based system. Five hundred ninety-five primi- and multiparous cows were randomly selected from 12 commercial Irish dairy farms and recruited for the study. Recruited cows were mobility scored and passed through a foot-paring crate where all 4 feet were lifted for examination. The team recorded the anatomical location and severity of any foot lesions present based on appearance only. Then, based on the type and severity of the lesions present, cows were classified according to 3 case definitions case definition 1: Any lesion present; case definition 2: Moderate lesions present (excluding minor lesions expected to have a low probability of affecting gait); and case definition 3: Severe lesions present (only including lesions most likely to result in a detectable gait abnormality). Sensitivity and Sp of MSc was calculated based on a threshold of MSc ≥2, defined as impaired (MSc = 2) or severely impaired (MSc = 3) mobility for each of the 3 case definitions, at the overall level and disaggregated by parity. The overall cow-level lesion prevalence based on the case definition 1 was 0.54 with significant between-herd variation. The overall Se and Sp of MSc for the detection of foot lesions were 0.18 and 0.96, 0.35 and 0.94, 0.43 and 0.94 for the case definitions 1, 2, and 3, respectively. Our findings showed poor Se, but high Sp of MSc for the detection of cows with foot lesions in a pasture-based system.

A survey of foot disinfection practices for control of bovine digital dermatitis: Evaluating solution depth, footbath hygiene, and the potential of footbaths as infection reservoirs for Treponema species.

Bovine digital dermatitis remains a widespread endemic disease of dairy cattle worldwide. Footbathing is commonly used as a control measure and has significant economic and environmental impacts. Few studies document footbathing practices on dairy farms or evaluate their suitability for achieving foot disinfection. This study describes footbathing practices on 32 farms observed in the United Kingdom, Ireland, and the Netherlands. We measured solution depth throughout footbathing and observed levels below 7 cm on 9 out of 32 farms, which leads to inadequate foot coverage. Solution depth was associated with the number of cow passages and decreased by 1.2 cm for every 100 cow passages. We also describe levels of OM content (g/L) throughout footbathing as a proxy for footbath hygiene. Our data indicates that almost half of footbaths (15/32) became contaminated above the 20 g/L threshold to which veterinary biocides are tested for efficacy, and that OM content is associated with the number of cow passages per liter of footbathing solution provided. A multivariable mixed model predicted that 1 L of footbathing solution per cow should be sufficient to prevent excess contamination. As a further measure of hygiene, we tested a subset of footbath samples to quantify the amount of DNA present from the Treponema species which are considered instrumental in the etiology of digital dermatitis. We did not detect Treponema DNA in footbath samples, which suggested they are unlikely to act as infection reservoirs for this disease. Multivariable mixed models including farm identity as a random effect demonstrated that for both change in solution depth and OM content the effect of farm-level factors was large. Because of the magnitude of this farm effect, applying model predictions will not translate to adequate solution depth and hygiene on all farms. Our data highlights the importance of footbath auditing on individual farms.