Modelling the impact of wastewater flows and management practices on antimicrobial resistance in dairy farms.

Dairy slurry is a major source of environmental contamination with antimicrobial resistant genes and bacteria. We developed mathematical models and conducted on-farm research to explore the impact of wastewater flows and management practices on antimicrobial resistance (AMR) in slurry. Temporal fluctuations in cephalosporin-resistant Escherichia coli were observed and attributed to farm activities, specifically the disposal of spent copper and zinc footbath into the slurry system. Our model revealed that resistance should be more frequently observed with relevant determinants encoded chromosomally rather than on plasmids, which was supported by reanalysis of sequenced genomes from the farm. Additionally, lower resistance levels were predicted in conditions with lower growth and higher death rates. The use of muck heap effluent for washing dirty channels did not explain the fluctuations in cephalosporin resistance. These results highlight farm-specific opportunities to reduce AMR pollution, beyond antibiotic use reduction, including careful disposal or recycling of waste antimicrobial metals.

Predictive modelling of deviation from expected milk yield in transition cows on automatic milking systems.

The transition period is a pivotal time in the production cycle of the dairy cow. It is estimated that between 30% and 50% of all cows experience metabolic or infectious disease during this time. One of the most common and economically consequential effects of disease during the transition period is a reduction in early lactation milk production. This has led to the utilisation of deviation from expected milk yield in early lactation as a proxy measure for transition health. However, to date, this analysis has been used exclusively for the retrospective assessment of transition cow health. Statistical models capable of predicting deviations from expected milk yield may allow producers to proactively manage animals predicted to suffer negative deviations in early lactation milk production. The objective of this retrospective cohort study was first, to explore the accuracy with which cow-level production and behaviour data collected on automatic milking systems (AMS) from 1-3 days in milk (DIM) can predict deviation from expected 30-day cumulative milk yield in multiparous cows. And second, to assess the accuracy with which predicted yield deviations can classify cows into groups which may facilitate improved transition management. Production, rumination, and physical activity data from 31 commercial AMS were accessed. A 3-step analytical procedure was then conducted. In Step 1, expected cumulative yield for 1-30 DIM for each individual cow-lactation was calculated using a mixed effect linear model. In Step 2, 30-Day Yield Deviation (YD) was calculated as the difference between observed and expected cumulative yield. Lactations were then assigned to one of three groups based on their YD, RED Group (0% YD). In Step 3, yield, rumination, and physical activity data from days 1-3 in lactation were used to predict YD using machine learning models. Following external validation, YD was predicted across the test data set with a mean absolute error of 9%. Categorisation of animals suffering large negative deviations (RED group) was achieved with a specificity of 99%, sensitivity of 35%, and balanced accuracy of 67%. Our results suggest that milk yield, rumination and physical activity patterns expressed by dairy cows from 1-3 DIM have utility in the prediction of deviation from expected 30-day cumulative yield. However, these predictions currently lack the sensitivity required to classify cows reliably and completely into groups which may facilitate improved transition cow management.

Antimicrobial resistance in dairy slurry tanks: A critical point for measurement and control.

Waste from dairy production is one of the largest sources of contamination from antimicrobial resistant bacteria (ARB) and genes (ARGs) in many parts of the world. However, studies to date do not provide necessary evidence to inform antimicrobial resistance (AMR) countermeasures. We undertook a detailed, interdisciplinary, longitudinal analysis of dairy slurry waste. The slurry contained a population of ARB and ARGs, with resistances to current, historical and never-used on-farm antibiotics; resistances were associated with Gram-negative and Gram-positive bacteria and mobile elements (ISEcp1, Tn916, Tn21-family transposons). Modelling and experimental work suggested that these populations are in dynamic equilibrium, with microbial death balanced by fresh input. Consequently, storing slurry without further waste input for at least 60 days was predicted to reduce ARB spread onto land, with > 99 % reduction in cephalosporin resistant Escherichia coli. The model also indicated that for farms with low antibiotic use, further reductions are unlikely to reduce AMR further. We conclude that the slurry tank is a critical point for measurement and control of AMR, and that actions to limit the spread of AMR from dairy waste should combine responsible antibiotic use, including low total quantity, avoidance of human critical antibiotics, and choosing antibiotics with shorter half-lives, coupled with appropriate slurry storage.

Use of Non-Steroidal Anti-Inflammatory Drugs and Attitudes to Pain in Pasture-Based Dairy Cows: A Comparative Study of Farmers and Veterinarians.

Pain is a significant welfare concern within the dairy industry. Recognizing and managing pain are important factors for safeguarding animal welfare. A questionnaire was sent via post to Irish dairy farmers and large animal veterinarians to assess attitudes to pain and the use of non-steroidal anti-inflammatory drugs (NSAIDs) in pasture-based dairy cows. The questionnaire could also be completed online. A total of 1,002 surveys were received from dairy farmers and 116 from livestock veterinarians. Veterinarians and farmers generally perceived the same conditions and procedures as the most painful. However, farmers scored surgical procedures significantly higher than veterinarians, and veterinarians scored lameness-related conditions, mastitis (clots in milk only) and hock hair loss significantly higher than farmers. Higher pain scores for conditions and procedures given by dairy farmers and veterinarians were associated with increased NSAID use. However, the use of NSAIDs was low, relative to the pain score, for Burdizzo castration (farmers and veterinarians), white line separation (farmers and veterinarians) and abscess (veterinarians), mastitis with clots in milk only (farmers) and calving with no assistance (farmers). Veterinarians who graduated less recently had significantly lower odds of using NSAIDs, and farmers that completed the survey online, had a larger herd size, completed education up to level four or five (as opposed to level three) and those who seemed to have less knowledge on analgesics, had significantly lower odds of using NSAIDs. Empathy was not found to be associated with NSAID use and no correlation was found between pain and empathy scores. Veterinarians perceived cost as more of a barrier than farmers did; therefore, NSAIDs should be offered more readily. For those working with dairy cows, there is a need to continue education on the benefits of analgesia, especially for conditions and procedures that have low NSAID use relative to pain score. The habituation of humans to pain in animals needs to be prevented to enable pain to be recognized and managed appropriately. Pain scores can be used as a benchmark for veterinarians and farmers to determine how their perception of pain compares to others, and see how this may influence their NSAID use.

The effect of environmental temperature on average daily gain in preweaned calves: A randomized controlled trial and Bayesian analysis.

Neonatal calves are relatively susceptible to heat loss, and previous research suggests that reduced environmental temperatures are associated with reduced average daily gain (ADG) during the preweaning phase. Current methods of mitigating negative effects of colder environmental conditions include the use of calf jackets and the provision of supplementary heat sources; however, previous research is limited. The aim of this study was to evaluate the effect of calf jackets and 1-kW heat lamps on the growth rates of preweaning calves and evaluate associations between environmental temperature and ADG using a Bayesian approach to incorporate both current and previous data. Seventy-nine calves from a single British dairy farm were randomly allocated at birth to 1 of the following 4 groups: no jacket and no heat lamp, heat lamp but no jacket, jacket but no heat lamp, or both heat lamp and jacket between January and April of 2021. Calves were weighed at both birth and at approximately 21 d of age. Temperature was recorded both inside and outside of the calf building, and in pens both with and without heat lamps using data loggers. To explore the effect of treatment group and environmental temperature on ADG, a fixed effects model was fitted over 1,000 bootstrap samples. The effect of environmental temperature on ADG was further explored within a Bayesian framework that used temperature and ADG data for 484 calves from 16 farms available from a previous trial as prior information. Calves housed under a 1-kW heat lamp had an increased ADG of 0.09 kg/d (95% bootstrap confidence interval: -0.02 to 0.20 kg/d), and no effect of jacket or interactions between jacket and heat lamp were found. A significant positive association was identified between the mean environmental temperature of the calf building and ADG, with a 1°C increase in temperature being associated with a 0.03 kg/d increase in ADG (95% bootstrap confidence interval: 0.01 to 0.04 kg/d). Associations between environmental temperature and ADG were further evaluated within a Bayesian framework, and posterior estimates were 0.014 kg/d of ADG per 1°C increase (95% credible interval: 0.009 to 0.021 kg/d). This study demonstrated that a 1-kW heat lamp was effective in increasing ADG in calves, and no significant effect of calf jacket on ADG was found. A significant, positive effect of increased pen temperature on calf ADG was identified in this study and was reinforced when including prior information from previous research within a Bayesian framework.

Preventive hoof trimming in dairy cattle: Determining current practices and identifying future research areas.

BACKGROUND: The extent to which preventive hoof trimming is implemented on Great Britain's (GB) dairy farms is unknown. The aims of this study were to determine common practices and capture producers' input on key areas that require further research. METHODS: An online survey was conducted over a 4-week period from March to April 2017. RESULTS: A total of 338 valid survey responses were received. The majority of farmers undertook preventive hoof trimming (82.4%), and this was significantly positively associated with increased herd yield (p < 0.001). Drying off was the most common time trimming was undertaken, with 72.2% of farmers who implemented preventive trimming doing so at this point in the management cycle. Of those undertaking preventive trimming, 46.4% solely used an external hoof trimmer, 31.7% solely used farm staff and the remainder (21.9%) used a combination of operators. Four over-arching themes were identified within the key research questions; when to trim, why we should trim, how to trim and who to trim. The most frequent questions related to optimal trimming timing, frequency and method. CONCLUSION: This study highlighted that preventive hoof trimming is a widespread practice on GB dairy farms, undertaken by both external hoof trimmers and farm staff. Despite this, farmers still want to know when they should undertake preventive hoof trimming and which technique they should use.

Improving growth rates in preweaning calves on dairy farms: A randomized controlled trial.

Previous research has identified key factors associated with improved average daily gain (ADG) in preweaning dairy calves and these factors have been combined to create a web app-based calf health plan (www.nottingham.ac.uk/herdhealthtoolkit). A randomized controlled trial was conducted to determine the effect of implementing this evidence-based calf health plan on both productivity and health outcomes for calves reared on British dairy farms. Sixty dairy farms were randomized by location (North, South, and Midlands) to either receive the plan at the beginning (INT) or after the end of the trial (CON) and recorded birth and weaning weights by weigh tape, and cases of morbidity and mortality. Calf records were returned for 3,593 calves from 45 farms (21 CON, 24 INT), with 1,760 calves from 43 farms having 2 weights recorded >40 d apart for ADG calculations, with 1,871 calves from 43 farms born >90 d before the end of the trial for morbidity and mortality calculations. Associations between both intervention group and the number of interventions in place with ADG were analyzed using linear regression models. Morbidity and mortality rates were analyzed using beta regression models. Mean ADG was 0.78 kg/d, ranging from 0.33 to 1.13 kg/d, with mean rates of 20.12% (0-96.55%), 16.40% (0-95.24%), and 4.28% (0-18.75%) for diarrhea, pneumonia, and mortality. The INT farms were undertaking a greater number of interventions (9.9) by the end of the trial than CON farms (7.6). Mean farm ADG was higher for calves on INT farms than CON farms for both male beef (MB, +0.22 kg/d) and dairy heifer (DH, +0.03 kg/d) calves. The MB calves on INT farms had significantly increased mean ADG (0.12 kg/d, 95% confidence interval: 0.02-0.22) compared with CON farms. No significant differences were observed between intervention groups for morbidity or mortality. Implementing one additional intervention from the plan, regardless of intervention group, was associated with improvements in mean ADG for DH calves of 0.01 kg/d (0.01, 0-0.03) and MB calves of 0.02 kg/d (0.00-0.04). Model predictions suggest that a farm with the highest number of interventions in place (15) compared with farms with the lowest number of interventions in place (4) would expect an improvement in growth rates from 0.65 to 0.81 kg/d for MB, from 0.73 to 0.88 kg/d for DH, a decrease in mortality rates from 10.9% to 2.8% in MB, and a decrease in diarrhea rates from 42.1% to 15.1% in DH. The calf health plan tested in this study represents a useful tool to aid veterinarians and farmers in the implementation of effective management interventions likely to improve the growth rates, health, and welfare of preweaning calves on dairy farms.

Evaluation of the use of antibiotic waste bins and medicine records to quantify antibiotic use on sheep, beef, and mixed species farms: A mixed methods study.

There is a lack of robust data on antibiotic use on sheep and beef farms in the UK, particularly for farms with mixed species. On mixed farms, quantification of antibiotic use is reliant on accurate farmers' records as veterinary prescription data does not provide information at the species level. Previous studies that have investigated multiple antibiotic use collection methods were conducted on single species farms and failed to collect data on the reasons why differences in methods may exist. This study aimed to evaluate sheep and beef farmers' antibiotic recording practices by comparing quantities of antibiotics measured from medicine records and empty antibiotic packaging collection bins, and identify barriers and facilitators of the antibiotic use collection methods. Thirty-five farms were followed for a year period. Farmers were asked to record their antibiotic treatments and deposit empty antibiotic packaging used in sheep or beef cattle into a bin. Semi-structured qualitative interviews were conducted to understand the experiences of farmers taking part in the study and explore the possible differences in methods. Bins and medicine records were collected and the mass of active ingredient (mg) was calculated. The level of agreement between the two antibiotic use collection methods was measured using rank parameters of Kendall's Ta. The bins were 67 % (CI = 29-87 %) more likely to measure more antibiotic use than the medicine records. The scale of variability of the measurements between two random farms was 33 % (CI = 6-56 %) larger for the antibiotic waste bins than the scale of variability between the medicine records. Sheep farmers often missed neonatal lamb treatments off their medicine records, with a median of 32.5 missing treatments per farm (IQR = 18-130). Of the mixed species farms, 28 % of treatment entries were missing the species the antibiotic was used in. Farmers reported that the bin was easy to use but they also reported that there was a tendency to under-report actual use where there were multiple workers on the farm or where treatments were administered by the veterinarian. The qualitative analysis identified contextual barriers to accurate medicine recording, such as difficulties with animal identification, with recording in the field, and with recording during lambing time. This study demonstrated that there were significant differences in antibiotic use measured by the bins and the medicine records. The mixed-methods approach provided an understanding of the contextual barriers that impacted farmers' medicine recording and use of the bin. This information on the contextual barriers can be used to inform the design of data collection methods to improve antibiotic consumption data in the sheep and beef sectors.

From the other perspective: Behavioural factors associated with UK sheep farmers' attitudes towards antibiotic use and antibiotic resistance.

Research suggests that many sheep farmers continue to carry out traditional antibiotic use practices despite new 'good practice' recommendations. The aim of this study was to group farmers depending on their attitudes around antibiotic use and antibiotic resistance, and determine the behaviours that are associated with the farmers in these groups. In 2017, a flock health survey was sent to British sheep farmers. K-means cluster analysis was used to identify groups of farmers with similar attitudes towards antibiotic use and resistance. A multivariable logistic regression model was built to determine the associations between farmers' past behaviours and their antibiotic attitude group. There were 461 responses. Two groups of farmers were identified based on their antibiotic attitudes. Cluster 1 were defined as the "discordant" group who had positive views of using antibiotics prophylactically and negative views of reducing antibiotic use. Cluster 2 were defined as the "concordant" group who were positive about reducing antibiotic use and had negative views about using antibiotics prophylactically. Using antibiotics in all lambs (OR = 2.689, CI = 1.571, 4.603), using antibiotics in all ewes (OR = 3.388, CI = 1.318, 8.706), always trimming diseased feet over the past three years (OR = 2.487, CI = 1.459, 4.238), not using a computer to record information over the past three years (OR = 1.996, CI = 1.179, 3.381), not changing worming practices over the past three years (OR = 1.879, CI = 1.144, 3.087), and farmers' perceptions that their sheep flock did not make a financial loss in the past three years (OR = 2.088, CI = 1.079, 4.040) were significantly associated with belonging to the discordant group. Talking to their veterinarian about antibiotic use or the frequency of veterinary visits were not associated with antibiotic attitude group. These results suggest that farmers who had attitudes relating to antibiotic use that did not align with current recommendations carried out more traditional practices, which were strengthened by their positive perceptions of profitability.

Assessing the Feasibility of Retrospective and Prospective Clinical Audit in Farm Animal Veterinary Practice.

As a quality improvement tool, clinical audit has been extensively described in the medical literature. There is scant literature on the use of clinical audit in the farm animal veterinary setting. This study describes the process and feasibility of prospective and retrospective data collection for farm animal clinical audit performed at three different farm animal practices in the United Kingdom. Retrospective clinical audit was difficult in all three practices due to barriers in establishing diagnosis and patient identity from clinical records. Prospective data collection proved feasible but depended on adequate case accrual and practitioner engagement. The decision to conduct clinical audit retrospectively or prospectively will depend on the topic to audit, the availability of data and the wishes of the team members involved. Further work is required looking at the use of clinical coding and alternatives to using practice management software to improve retrospective data availability for clinical audit.

Ropporin-1 and 1B Are Widely Expressed in Human Melanoma and Evoke Strong Humoral Immune Responses.

Antibodies that block immune regulatory checkpoints (programmed cell death 1, PD-1 and cytotoxic T-lymphocyte-associated antigen 4, CTLA-4) to mobilise immunity have shown unprecedented clinical efficacy against cancer, demonstrating the importance of antigen-specific tumour recognition. Despite this, many patients still fail to benefit from these treatments and additional approaches are being sought. These include mechanisms that boost antigen-specific immunity either by vaccination or adoptive transfer of effector cells. Other than neoantigens, epigenetically regulated and shared antigens such as NY-ESO-1 are attractive targets; however, tissue expression is often heterogeneous and weak. Therefore, peptide-specific therapies combining multiple antigens rationally selected to give additive anti-cancer benefits are necessary to achieve optimal outcomes. Here, we show that Ropporin-1 (ROPN1) and 1B (ROPN1B), cancer restricted antigens, are highly expressed and immunogenic, inducing humoral immunity in patients with advanced metastatic melanoma. By multispectral immunohistochemistry, 88.5% of melanoma patients tested (n = 54/61) showed ROPN1B expression in at least 1 of 2/3 tumour cores in tissue microarrays. Antibody responses against ROPN1A and ROPN1B were detected in 71.2% of melanoma patients tested (n = 74/104), with increased reactivity seen with more advanced disease stages. Thus, ROPN1A and ROPN1B may indeed be viable targets for cancer immunotherapy, alone or in combination with other cancer antigens, and could be combined with additional therapies such as immune checkpoint blockade.

Factors associated with daily weight gain in preweaned calves on dairy farms.

The preweaning period is vital in the development of calves on dairy farms and improving daily liveweight gain (DLWG) is important to both financial and carbon efficiency; minimising rearing costs and improving first lactation milk yields. In order to improve DLWG, veterinary advisors should provide advice that has both a large effect size as well as being consistently important on the majority of farms. Whilst a variety of factors have previously been identified as influencing the DLWG of preweaned calves, it can be challenging to determine their relative importance, which is essential for optimal on-farm management decisions. Regularised regression methods such as ridge or lasso regression provide a solution by penalising variable coefficients unless there is a proportional improvement in model performance. Elastic net regression incorporates both lasso and ridge penalties and was used in this research to provide a sparse model to accommodate strongly correlated predictors and provide robust coefficient estimates. Sixty randomly selected British dairy farms were enrolled to collect weigh tape data from preweaned calves at birth and weaning, resulting in data being available for 1014 calves from 30 farms after filtering to remove poor quality data, with a mean DLWG of 0.79 kg/d (range 0.49-1.06 kg/d, SD 0.13). Farm management practices (e.g. colostrum, feeding, hygiene protocols), building dimensions, temperature/humidity and colostrum quality/bacteriology data were collected, resulting in 293 potential variables affecting farm level DLWG. Bootstrapped elastic net regression models identified 17 variables as having both a large effect size and high stability. Increasing the maximum preweaned age within the first housing group (0.001 kg/d per 1d increase, 90 % bootstrap confidence interval (BCI): 0.000-0.002), increased mean environmental temperature within the first month of life (0.012 kg/d per 1 °C increase, 90 % BCI: 0.002-0.037) and increased mean volume of milk feeding (0.012 kg/d per 1 L increase, 90 % BCI: 0.001-0.024) were associated with increased DLWG. An increase in the number of days between the cleaning out of calving pen (-0.001 kg/d per 1d increase, 90 % BCI: -0.001-0.000) and group housing pens (-0.001 kg/d per 1d increase, 90 % BCI: -0.002-0.000) were both associated with decreased DLWG. Through bootstrapped elastic net regression, a small number of stable variables have been identified as most likely to have the largest effect size on DLWG in preweaned calves. Many of these variables represent practical aspects of management with a focus around stocking demographics, milk/colostrum feeding, environmental hygiene and environmental temperature; these variables should now be tested in a randomised controlled trial to elucidate causality.

Quantitative Analysis of Colostrum Bacteriology on British Dairy Farms.

Total bacterial counts (TBC) and coliform counts (CC) were estimated for 328 colostrum samples from 56 British dairy farms. Samples collected directly from cows' teats had lower mean TBC (32,079) and CC (21) than those collected from both colostrum collection buckets (TBC: 327,879, CC: 13,294) and feeding equipment (TBC: 439,438, CC: 17,859). Mixed effects models were built using an automated backwards stepwise process in conjunction with repeated bootstrap sampling to provide robust estimates of both effect size and 95% bootstrap confidence intervals (BCI) as well as an estimate of the reproducibility of a variable effect within a target population (stability). Colostrum collected using parlor (2.06 log cfu/ml, 95% BCI: 0.35-3.71) or robot (3.38 log cfu/ml, 95% BCI: 1.29-5.80) milking systems, and samples collected from feeding equipment (2.36 log cfu/ml, 95% BCI: 0.77-5.45) were associated with higher TBC than those collected from the teat, suggesting interventions to reduce bacterial contamination should focus on the hygiene of collection and feeding equipment. The use of hot water to clean feeding equipment (-2.54 log cfu/ml, 95% BCI: -3.76 to -1.74) was associated with reductions in TBC, and the use of peracetic acid (-2.04 log cfu/ml, 95% BCI: -3.49 to -0.56) or hypochlorite (-1.60 log cfu/ml, 95% BCI: -3.01 to 0.27) to clean collection equipment was associated with reductions in TBC compared with water. Cleaning collection equipment less frequently than every use (1.75 log cfu/ml, 95% BCI: 1.30-2.49) was associated with increased TBC, the use of pre-milking teat disinfection prior to colostrum collection (-1.85 log cfu/ml, 95% BCI: -3.39 to 2.23) and the pasteurization of colostrum (-3.79 log cfu/ml, 95% BCI: -5.87 to -2.93) were associated with reduced TBC. Colostrum collection protocols should include the cleaning of colostrum collection and feeding equipment after every use with hot water as opposed to cold water, and hypochlorite or peracetic acid as opposed to water or parlor wash. Cows' teats should be prepared with a pre-milking teat disinfectant and wiped with a clean, dry paper towel prior to colostrum collection, and colostrum should be pasteurized where possible.

A recommended "minimum data set" framework for SD-OCT retinal image acquisition and analysis from the Atlas of Retinal Imaging in Alzheimer's Study (ARIAS).

INTRODUCTION: We propose a minimum data set framework for the acquisition and analysis of retinal images for the development of retinal Alzheimer's disease (AD) biomarkers. Our goal is to describe methodology that will increase concordance across laboratories, so that the broader research community is able to cross-validate findings in parallel, accumulate large databases with normative data across the cognitive aging spectrum, and progress the application of this technology from the discovery stage to the validation stage in the search for sensitive and specific retinal biomarkers in AD. METHODS: The proposed minimum data set framework is based on the Atlas of Retinal Imaging Study (ARIAS), an ongoing, longitudinal, multi-site observational cohort study. However, the ARIAS protocol has been edited and refined with the expertise of all co-authors, representing 16 institutions, and research groups from three countries, as a first step to address a pressing need identified by experts in neuroscience, neurology, optometry, and ophthalmology at the Retinal Imaging in Alzheimer's Disease (RIAD) conference, convened by the Alzheimer's Association and held in Washington, DC, in May 2019. RESULTS: Our framework delineates specific imaging protocols and methods of analysis for imaging structural changes in retinal neuronal layers, with optional add-on procedures of fundus autofluorescence to examine beta-amyloid accumulation and optical coherence tomography angiography to examine AD-related changes in the retinal vasculature. DISCUSSION: This minimum data set represents a first step toward the standardization of retinal imaging data acquisition and analysis in cognitive aging and AD. A standardized approach is essential to move from discovery to validation, and to examine which retinal AD biomarkers may be more sensitive and specific for the different stages of the disease severity spectrum. This approach has worked for other biomarkers in the AD field, such as magnetic resonance imaging; amyloid positron emission tomography; and, more recently, blood proteomics. Potential context of use for retinal AD biomarkers is discussed.

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.

Antimicrobial use practices and opinions of beef farmers in England and Wales.

BACKGROUND: Limited research exists on antimicrobial use practices of beef farmers. This study aimed to investigate antimicrobial practices and perceptions of beef farmers in England and Wales, and identify drivers of higher antimicrobial use for treatment of bovine pneumonia. METHODS: A survey was sent out in 2017 to beef farmers in England and Wales who supply to two abattoirs. Descriptive statistics were used to summarise the data. A logistic regression model was built to determine factors associated with treating greater than 5 per cent of the predominant group in the herd with antimicrobials for pneumonia. RESULTS: There were a total of 171 useable responses. Most farmers reported using antimicrobials in less than 5 per cent of their herd for the treatment of common diseases. Most farmers (90 per cent) reported that they understood what antimicrobial resistance means, but only 55 per cent were aware of critically important antimicrobials and 9 per cent could name at least one critically important antimicrobial. Having a calf-rearing enterprise and not considering Johne's disease when buying in cattle were associated with using antimicrobials to treat pneumonia in greater than 5 per cent of the predominant group in the herd. CONCLUSION: Self-reported antimicrobial use appears to be low in beef farms. However, some gaps in understanding aspects of antimicrobial stewardship by farmers were identified.

Automated prediction of mastitis infection patterns in dairy herds using machine learning.

Mastitis in dairy cattle is extremely costly both in economic and welfare terms and is one of the most significant drivers of antimicrobial usage in dairy cattle. A critical step in the prevention of mastitis is the diagnosis of the predominant route of transmission of pathogens into either contagious (CONT) or environmental (ENV), with environmental being further subdivided as transmission during either the nonlactating "dry" period (EDP) or lactating period (EL). Using data from 1000 farms, random forest algorithms were able to replicate the complex herd level diagnoses made by specialist veterinary clinicians with a high degree of accuracy. An accuracy of 98%, positive predictive value (PPV) of 86% and negative predictive value (NPV) of 99% was achieved for the diagnosis of CONT vs ENV (with CONT as a "positive" diagnosis), and an accuracy of 78%, PPV of 76% and NPV of 81% for the diagnosis of EDP vs EL (with EDP as a "positive" diagnosis). An accurate, automated mastitis diagnosis tool has great potential to aid non-specialist veterinary clinicians to make a rapid herd level diagnosis and promptly implement appropriate control measures for an extremely damaging disease in terms of animal health, productivity, welfare and antimicrobial use.

Quantitative analysis of calf mortality in Great Britain.

National bodies in Great Britain (GB) have expressed concern over young stock health and welfare and identified calf survival as a priority; however, no national data have been available to quantify mortality rates. The aim of this study was to quantify the temporal incidence rate, distributional features, and factors affecting variation in mortality rates in calves in GB since 2011. The purpose was to provide information to national stakeholder groups to inform resource allocation both for knowledge exchange and future research. Cattle birth and death registrations from the national British Cattle Movement Service were analyzed to determine rates of both slaughter and on-farm mortality. The number of births and deaths registered between 2011 and 2018 within GB were 21.2 and 21.6 million, respectively. Of the 3.3 million on-farm deaths, 1.8 million occurred before 24 mo of age (54%) and 818,845 (25%) happened within the first 3 mo of age. The on-farm mortality rate was 3.87% by 3 mo of age, remained relatively stable over time, and was higher for male calves (4.32%) than female calves (3.45%). Dairy calves experience higher on farm mortality rates than nondairy (beef) calves in the first 3 mo of life, with 6.00 and 2.86% mortality rates, respectively. The 0- to 3-mo death rate at slaughterhouse for male dairy calves has increased from 17.40% in 2011 to 26.16% in 2018, and has remained low (<0.5%) for female dairy calves and beef calves of both sexes. Multivariate adaptive regression spline models were able to explain a large degree of the variation in mortality rates (coefficient of determination = 96%). Mean monthly environmental temperature and month of birth appeared to play an important role in neonatal on-farm mortality rates, with increased temperatures significantly reducing mortality rates. Taking the optimal month of birth and environmental temperature as indicators of the best possible environmental conditions, maintaining these conditions throughout the year would be expected to result in a reduction in annual 0- to 3-mo mortality of 37,571 deaths per year, with an estimated economic saving of around £11.6 million (USD $15.3 million) per annum. National cattle registers have great potential for monitoring trends in calf mortality and can provide valuable insights to the cattle industry. Environmental conditions play a significant role in calf mortality rates and further research is needed to explore how to optimize conditions to reduce calf mortality rates in GB.

Viral Shedding in Recipients of Live Attenuated Influenza Vaccine in the 2016-2017 and 2017-2018 Influenza Seasons in the United Kingdom.

BACKGROUND: The (H1N1)pdm09 live attenuated influenza vaccine (LAIV) strain was changed for the 2017-2018 influenza season to improve viral fitness, following poor protection against (H1N1)pdm09 viruses in 2015-2016. We conducted LAIV virus shedding studies to assess the effect of this change. METHODS: Children aged 2-18 years were recruited to receive LAIV in the 2016-2017 (n = 641) and 2017-2018 (n = 362) influenza seasons. Viruses from nasal swabs taken 1, 3, and 6 days postvaccination were quantified by reverse-transcription polymerase chain reaction and area under the curve titers were determined. Presence and quantity of shedding were compared between strains and seasons with adjustment for age and prior LAIV (n = 436), inactivated seasonal vaccine (n = 100), or (H1N1)pdm09 vaccine (n = 166) receipt. RESULTS: (H1N1)pdm09 detection (positivity) in 2016-2017 and 2017-2018 (11.2% and 3.9%, respectively) was lower than that of H3N2 (19.7% and 18.7%, respectively) and B/Victoria (28.9% and 33.9%, respectively). (H1N1)pdm09 positivity was higher in 2016-2017 than 2017-2018 (P = .005), but within shedding-positive participants, the (H1N1)pdm09 titer increased in 2017-2018 (P = .02). H3N2 and influenza B titers were similar between seasons. Positivity declined with age, and prior vaccination reduced the likelihood of shedding influenza B but not (H1N1)pdm09. CONCLUSIONS: The (H1N1)pdm09 titer increased in 2017-2018, indicating more efficient virus replication in shedding-positive children than the 2016-2017 strain, although overall positivity was reduced. Age and vaccination history require consideration when correlating virus shedding and protection. CLINICAL TRIALS REGISTRATION: NCT02143882, NCT02866942, and NCT03104790.

Association of lameness and mastitis with return-to-service oestrus detection in the dairy cow.

Oestrus detection is an important part of maintaining efficient reproductive performance in dairy herds. Both lameness and mastitis are common diseases of dairy cows that may impact oestrus detection. A set of data from 28 herds identified as having good recording of clinical mastitis and lameness incidents was used for the study. Logistic regression was used to identify associations between disease episodes within 100 days of insemination and changes in the probability of reinsemination at either 18-24 or 19-26 days after an unsuccessful insemination. Population attributable risk was calculated to understand the impact these diseases may have at a herd level. Lameness 0-28 days after the first insemination of the interval decreased the odds of a reinsemination at an appropriate time by approximately 20 per cent. Clinical mastitis 1-28 days prior to the first insemination of the interval increased the odds of reinsemination at the expected time by approximately 20 per cent. The associations were similar for either interservice interval outcome. Population attributable risk suggested that the effect of these diseases on the probability of reinsemination at the expected time at a population level would likely be extremely small.