Performance of various interpretations of clinical scoring systems for diagnosis of respiratory disease in dairy calves in a temperate climate using Bayesian latent class analysis.

Bovine respiratory disease (BRD) presents a challenge to farmers all over the globe, not only because it can have significant impacts on welfare and productivity, but also because diagnosis can prove challenging. Several clinical scoring systems have been developed to aid farmers in making consistent early diagnosis, 2 examples being the Wisconsin (WCS) and the California (CALIF) systems. Neither of these systems were developed in or for use in a temperate environment. As environment may lead to changes in BRD presentation, the weightings and cutoffs designed for one environmental presentation of BRD may not be appropriate when used in a temperate climate. Additionally, the interpretation of the scores recorded varies between studies; this may also influence conclusions. Hence, the objective of this work was to investigate the sensitivity (Se) and specificity (Sp) of these tests in a temperate climate and investigate the influence of varying the interpretation on the performance of the WCS. In this prospective study, 98 commercial spring-calving dairy farms were recruited (40 randomly, 58 targeted) and visited. Thoracic ultrasound and WCS were performed on 20 randomly sampled calves between 4 and 6 wk of age on each farm. On a subset of 32 farms, the CALIF score was also undertaken. The data were then used in a hierarchical Bayesian latent class model to estimate the Se and Sp of 5 different interpretations of the Wisconsin clinical score and 1 interpretation of the California clinical score. In total, 1,936 calves were examined. The Se of the Wisconsin score varied from 0.336 to 0.577 depending on the interpretation used, and the Sp varied from 0.943 to 0.977. The Se of the California score was 0.563 (95% Bayesian credible interval [BCI]: 0.452, 0.681) and the Sp was 0.919 (95% BCI: 0.899, 0.937). In conclusion, the performances of the clinical scores in a temperate environment were similar to previously published work from more extreme climates; however, the performance varied widely depending on the score interpretation. Authors should justify their use of a particular clinical score interpretation to improve clarity in publications.

Recording antimicrobial use on Irish dairy farms: Barriers and facilitators to using technology and sharing data.

Antimicrobial use (AMU) data are essential to monitor the effect of AMU reduction strategies in animal health. The use of technology and herd recording software to record AMU will be vital to scale the collation of these data in the future. The aim of this study was to determine the barriers and facilitators to Irish dairy farmers recording their AMU using a herd recording software and sharing AMU data. Thirty-three Irish dairy farmers involved in a study on AMU monitoring were asked to record their AMU using a herd recording software over a 12-mo period. At the end of the 12-mo period, 10 of these farmers were selected to take part in semi-structured interviews exploring their opinions on recording AMU, the use of herd recording software, and sharing AMU data. Interviews were transcribed and qualitatively analyzed using inductive thematic analysis. Several barriers and facilitators to farmers recording their AMU using a herd recording software and sharing AMU data were identified. Barriers included the age and generation of the farmer, farm infrastructure, a lack of training and education, a lack of knowledge around the benefits of digital data, a lack of incentive to digitize records, and a fear of repercussions. Facilitators identified by the farmers included the benefits of having instantly available data for making herd management decisions, reduced paperwork, increased organization for inspections, and a potential positive effect on the image of the dairy industry. To increase the uptake of new technology to record AMU at farm-level, farmers will need support in terms of education and training around the software available to them and reassurance around the perceived risks of repercussions with sharing data in a digital format.

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.

Survey of farm, parlour and milking management, parlour technologies, SCC control strategies and farmer demographics on Irish dairy farms.

BACKGROUND: This cross-sectional study describes a survey designed to fill knowledge gaps regarding farm management practices, parlour management practices and implemented technologies, milking management practices, somatic cell count (SCC) control strategies, farmer demographics and attitudes around SCC management on a sample of Irish dairy farms. RESULTS: We categorized 376 complete responses by herd size quartile and calving pattern. The average respondent herd was 131 cows with most (82.2%) operating a seasonal calving system. The median monthly bulk tank somatic cell count for seasonal calving systems was 137,000 cells/ml (range 20,000 - 1,269,000 cells/ml), 170,000 cells/ml for split-calving systems (range 46,000 - 644,000 cells/ml) and 186,000 cells/ml for 'other' herds (range 20,000 - 664,000 cells/ml). The most common parlour types were swing-over herringbones (59.1%) and herringbones with recording jars (22.2%). The average number of units across herringbone parlours was 15, 49 in rotary parlours and two boxes on automatic milking system (AMS) farms. The most common parlour technologies were in-parlour feeding systems (84.5%), automatic washers on the bulk tank (72.8%), automatic cluster removers (57.9%), and entrance or exit gates controlled from the parlour pit (52.2%). Veterinary professionals, farming colleagues and processor milk quality advisors were the most commonly utilised sources of advice for SCC management (by 76.9%, 50.0% and 39.2% of respondents respectively). CONCLUSIONS: In this study, we successfully utilised a national survey to quantify farm management practices, parlour management practices and technology adoption levels, milking management practices, SCC control strategies and farmer demographics on 376 dairy farms in the Republic of Ireland. Rotary and AMS parlours had the most parlour technologies of any parlour type. Technology add-ons were generally less prevalent on farms with smaller herds. Despite finding areas for improvement with regard to frequency of liner changes, glove-wearing practices and engagement with bacteriology of milk samples, we also found evidence of high levels of documentation of mastitis treatments and high use of post-milking teat disinfection. We discovered that Irish dairy farmers are relatively content in their careers but face pressures regarding changes to the legislation around prudent antimicrobial use in their herds.

The impact of changing the cut-off threshold of the interferon-gamma (IFN-γ) assay for diagnosing bovine tuberculosis in Ireland.

In Ireland, the interferon-gamma (IFN-γ) assay is routinely used as an ancillary test interpreted in parallel with the single intradermal comparative tuberculin test (SICTT) to maximize the detection of bovine tuberculosis (bTB) infected animals. Up until 2018, a positive test result was recorded in the IFN-γ ELISA assay following whole blood stimulation with purified protein derivative (PPD)-bovine (B), PPD-avian (A) and nil sample (N), using the interpretation criteria, B-N > 50 optical density units (OD), B > 100 and B-A > 0. Following a review of available data, the threshold of the B-A component changed to B-A > 80. As predicting the impact of changing the cut-off thresholds for the IFN-γ test de novo is challenging, the aims of this study were to follow animals that initially tested negative using the new IFN-γ assay interpretation criteria and investigate their future risk of disclosure with bTB, with a focus on animals that otherwise would have been removed when using the older interpretation criteria (0 < B-A ≤ 80). Enrolled animals (n = 28,669 cattle from 527 herds) were followed up for two years (2019-2021), or to point of bTB detection or death. At the end of follow-up, 1151 (4.0%) of enrolled animals were bTB cases. The majority of these cases were diagnosed using SICTT (80.5%). The cumulative number of positive animals that would have been removed if the old cut-off (0 < B-A ≤ 80) was used amounted to 1680 cattle (5.9% of the enrolled cohort). Of these, 127 (7.5%) were diagnosed with bTB during follow-up. In contrast, 1024 of the 1151 cattle which subsequently tested positive during the study period following a negative IFN-γ test would not have been identified with the old or new IFN-γ cut-off criteria. Survival analysis showed that animals that would have been removed under the old interpretation criteria were at increased risk of a positive diagnosis with bTB during follow-up compared to other test negative animals. A newly developed risk prediction model (using a Cox proportional hazard model) showed that age, animal number of SICTT tests, number of inconclusive SICTT tests, B-A (IFN-γ assay), B-N (IFN-γ assay), animals from store herds and the percentage of the rest of the herd that were positive during the breakdown were statistically significantly associated with bTB detection. However, inclusion of the IFN-γ OD variables did not show added value in terms of prediction performance of the model.

Potential Application of SARS-CoV-2 Rapid Antigen Diagnostic Tests for the Detection of Infectious Individuals Attending Mass Gatherings - A Simulation Study.

Rapid Antigen Diagnostic Tests (RADTs) for the detection of SARS-CoV-2 offer advantages in that they are cheaper and faster than currently used PCR tests but have reduced sensitivity and specificity. One potential application of RADTs is to facilitate gatherings of individuals, through testing of attendees at the point of, or immediately prior to entry at a venue. Understanding the baseline risk in the tested population is of particular importance when evaluating the utility of applying diagnostic tests for screening purposes. We used incidence data from January and from July-August 2021, periods of relatively high and low levels of infection, to estimate the prevalence of infectious individuals in the community at particular time points and simulated mass gatherings by sampling from a series of age cohorts. Nine different illustrative scenarios were simulated, small (n = 100), medium (n = 1,000) and large (n = 10,000) gatherings each with 3 possible age constructs: mostly younger, mostly older or a gathering with equal numbers from each age cohort. For each scenario, we estimated the prevalence of infectious attendees, then simulated the likely number of positive and negative test results, the proportion of cases detected and the corresponding positive and negative predictive values, and the cost per case identified. Our findings suggest that for each reported case on a given day, there are likely to be 13.8 additional infectious individuals also present in the community. Prevalence ranged from 0.26% for "mostly older" events in July-August, to 2.6% for "mostly younger" events in January. For small events (100 attendees) the expected number of infectious attendees ranged from <1 across all age constructs of attendees in July-August, to 2.6 for "mostly younger" events in January. For large events (10,000 attendees) the expected number of infectious attendees ranged from 27 (95% confidence intervals 12 to 45) for mostly older events in July-August, to 267 (95% confidence intervals 134 to 436) infectious attendees for mostly younger attendees in January. Given rapid changes in SARS-CoV-2 incidence over time, we developed an RShiny app to allow users to run updated simulations for specific events.