The impact of glutaraldehyde based footbaths on Dichelobacter nodosus prevalence and the antimicrobial resistant community of the ovine interdigital skin.

Ovine footrot, is a highly contagious polymicrobial bacterial infection, primarily caused by Dichelobacter nodosus. Preventative bactericidal footbaths are commonly used in the sheep industry to reduce the spread of bacteria. However, their effect on the bacterial community is poorly understood. This is the first study to investigate the impact of 2% Digicur (ProGiene,UK) footbath on the bacterial community of the ovine interdigital skin following a common UK footbathing routine. Swab samples were analysed by qPCR to determine prevalence and load of D. nodosus and numerated on MacConkey agar in the presence or absence of tetracycline and ampicillin to determine phenotypic antimicrobial resistance. Metagenomics were used to determine the impact of a single footbath on the bacterial community and genotypic antimicrobial resistance. The results suggest 2% Digicur is ineffective at reducing the load of D. nodosus when applied as a one off or weekly footbath, however sheep may act as a reservoir for multi-drug resistant bacteria creating opportunities to spread antimicrobial resistance to other sheep and their environment.

Farmers' Perceptions of Preventing Antibiotic Resistance on Sheep and Beef Farms: Risk, Responsibility, and Action.

Antibiotic resistance is one of the most serious public health risks facing humanity. The overuse of antibiotics in the treatment of infectious disease have been identified as sources of the global threat of antibiotic resistance. This paper examines how farmers perceive and manage risks associated with overuse of antibiotics. Specifically, the paper examines the role of habitus and risk in determining farmers' decisions to adopt national antibiotic reduction targets set by members of the Responsible Use of Medicines in Agriculture Alliance's Targets Task Force. Semi-structured interviews were conducted with 34 sheep and beef farmers in England and Wales. Farmers presented four scripts which illuminated reasons for limited adoption of the targets. The scripts presented the farmers as "good farmers" facing an emerging threat to their ontological security. Scripts suggested that they engaged in preventative measures but deflected responsibility for reducing antibiotic resistance to veterinarians and poorly run farms. This research provides valuable insights for policy makers and highlight the benefits of including social science research to support effective implementation.

Use of bootstrapped, regularised regression to identify factors associated with lamb-derived revenue on commercial sheep farms.

The profitability of UK sheep farms is variable with many farms making a net loss. For economic sustainability, farms have to be profitable, therefore it is important to maximise income whilst controlling costs. The most important source of income in sheep flocks is from lamb production but there is little information on factors that explain variability between farms in revenue from lamb sales. The aim of this research was to identify farm, farmer and management factors likely to have the largest, most reliable associations with lamb-derived revenue. From a population of 830 sheep farms, 408 farmers completed an online questionnaire comprising over 300 variables. Total lamb-derived revenue was calculated for each farm using abattoir information including carcass classification. The median flock size was 560 ewes, median land size 265 acres, median revenue per acre from lambs sold was £197 (IQR = 120-296) and median revenue per ewe £95 (IQR = 72-123). A robust analytic approach using regularised (elastic net) regression with bootstrapping was implemented to account for multicollinearity in the data and to reduce the likelihood of model over-fitting. To provide model inference and allow ranking of variables in terms of relevance, covariate stability and coefficient distributions were evaluated. Factors with high stability and relatively large positive associations with revenue per acre were (median effect size (£); 95 % bootstrap probability interval); an increased stocking rate of 0.2 ewe/acre (13; 6-17), fertilizer being used on most of the grazing land (18; 0.1-37), the use of rotational grazing (13; 0.3-34), decreased proportion of ewes with prolapses (4; 0.3-9), separation of lame sheep from the rest of the flock (16; 0.9-37), selecting ewes for culling based on prolapses (20; 0.2-55) and infertility (20; 2-46), conducting body condition scoring of ewes at lambing (28; 3-58), early lactation (21; 1-54) or weaning (25; 2-70), increased farmer education (20; 2-54) and farmers with a positive business attitude (15; 0.2-38). Additional factors with a high stability and relatively large associations with increased revenue per ewe were; never trimming diseased feet of lame ewes (9; 0.8-22) and making use of farm records (5; 0.3-12). This is the first study in animal health epidemiology to use bootstrapped regularised regression to evaluate a wide dataset to provide a ranking of the importance of explanatory covariates. We conclude that the relatively small set of variables identified, with a potentially large influence on lamb-derived revenue, should be considered prime candidates for future intervention studies.