Vaccination is one of the most effective methods for the prevention of infectious diseases. Selected types of vaccines are administered to the majority of the population, thereby supporting herd immunity against certain transmissible diseases. Importantly, the immune response to vaccines - regarding its intensity, complexity, and duration - varies among individuals. These differences are partly influenced by genetic factors, specifically the presence of selected genetic polymorphisms that may affect not only the effectiveness of the immune response but also the risk of adverse reactions. Vaccinomics is a research field focused on the study of genomic and molecular biological characteristics of the human organism with the aim of elucidating the causes of interindividual differences in immune responses following vaccination. Adversomics deals with adverse reactions after vaccination. Vaccinomics may help to identify individuals who could benefit from alternative vaccination schedules or the selection of specific vaccine types. However, the majority of associations reported to date still require independent validation.

The aim of this study was to evaluate the efficacy of pour-on fluralaner formulations for the prevention of cutaneous myiasis caused by Cochliomyia hominivorax in newborn calves under field conditions. Three field trials were conducted in Argentina, including subtropical and temperate regions. In Trial 1, calves with unhealed navels were assigned to two fluralaner-treated groups with different commercial pour-on formulations and an untreated control group. In Trial 2, two groups of newborn calves were treated either with fluralaner pour-on or injectable doramectin. Trial 3, where 84 calves were also treated with a pour-on formulation of fluralaner, was performed in an island livestock farming systems located along the Paraná River, where extensive grazing conditions are extreme, and the operational difficulties associated with providing meticulous animal husbandry practices to prevent parasitic diseases in cattle are amplified. Animals were monitored daily for the occurrence of myiasis. In Trial 1, no cases of myiasis were recorded in fluralaner-treated calves, whereas all control animals became infested. In Trial 2, no infestations were observed in the fluralaner-treated group, while myiasis was recorded in 3.5% of calves treated with doramectin. In Trial 3, the prevalence of myiasis in fluralaner-treated calves was 7.1%, with most cases associated with treatments applied under rainy conditions. In contrast, a prevalence of 34.5% was recorded in the previous year in the same herd when treatment consisted of insecticidal formulations based on organophosphates and pyrethroid. No adverse effects associated with fluralaner treatment were observed in all treated calves. These results demonstrate the high efficacy of fluralaner pour-on formulations for the prevention of C. hominivorax myiasis in newborn calves under extensive production systems.

The intensive use of antiparasitic treatments, such as macrocyclic lactones, is known to affect non-target dung-inhabiting insects, leading to reduced community functioning and ecosystem services. We describe the development of a spatially explicit simulation to assess the effects of the treatment of different proportions of a livestock herd with anthelmintics, a strategy known as targeted selective treatment. We simulated the treatment of a varying proportion of a livestock herd with antiparasitics, and the effects inflicted on three dung-inhabiting insect guilds (flies, endocoprids and paracoprids) with novel life cycle, colonisation and dispersal mechanisms. We varied livestock stocking density to test the effect of dung availability on these effects. Complex population-level effects were seen as treatment varied, while increased stocking densities led to smaller community sizes overall. Dung removal, measured by total pat number and mean pat biomass, increased with decreasing livestock treatment at all stocking densities. These findings provide a theoretical basis for promoting targeted selective treatment with antiparasitics in an effort to balance livestock production and animal welfare with biodiversity and ecosystem functioning.

Pasture-based dairy systems are valued by consumers for allowing the expression of natural behaviors; however, evolving stakeholder expectations include the ability for cows to exercise agency and choice. This study examined whether dairy cows would choose to voluntarily exit their grazing paddock and walk to an independent treed area, and quantified visit patterns and their relationship to weather, paddock distance, behavior, and rumen temperature. Sixty mixed-aged Friesian-cross cows were randomly allocated to Treed (n = 2) and Reference (n = 2) herds from November 2024 to March 2025. On-animal measurement devices included collars (latitude, longitude, grazing, ruminating), leg-worn accelerometers (lying/standing), and rumen boluses (rumen temperature, drinking). Weather data included temperature, relative humidity, wind speed, rainfall, solar radiation, and a calculated grazing heat load index (GHLI). After familiarization to the treed areas, cows were monitored over 4 observation periods (the first was 23 d; remaining were 15 d) that varied in milking frequency (once/twice daily), supplementation (present/not present), and herd size (separate, 15 cows/herd; or combined, 30 cows/herd). Latitude-longitude data were used to define treed area visits (threshold of ≥ 80% of the herd present at any time > 10 min). Bayesian logistic regression models (Treed area herds only) examined whether weather variables (temperature, GHLI, solar radiation, humidity; each categorized at the 75th percentile into levels: 'below-threshold', lower 75%, and 'above-threshold', upper 25%) and distance predicted treed area visit probability. Bayesian generalized additive mixed models (GAMMs; all herds) examined hourly behaviors and rumen temperature, with fixed effects for 'visit status' (Treed area herd - No Visit, Treed area herd - Visit, Reference herd), GHLI level, and their interaction. Splines captured temporal patterns. Daily behavioral and rumen temperature summaries were derived from hourly predictions. Results were reported as odds ratios (OR), and median with 95% credible intervals (CrI). Treed area herds visited treed areas 3-22 times per observation period (1.1-2.1 visits on visit days), spending 0.9-5.5 h/d there. Use peaked in the afternoons, varied by herd and observation period, and occurred in both above- and below-threshold thermal conditions. Comparing visit and non-visit days within the Treed area herds showed that paddocks ≥ 250m from the treed area reduced visit odds by 56% compared with Paddocks < 250 m from the treed area (OR = 0.44, 95% CrI: 0.27-0.69). Further, above-threshold temperature (≥22°C) doubled visit odds compared with below-threshold (OR = 2.03, 95% CrI: 1.13-3.44). Comparison of Treed and Reference herds showed that during treed area visits when the GHLI was above-threshold (≥54) daily ruminating-while-standing doubled (4.7 vs 2.8 h/d, respectively), while hourly grazing (OR = 0.77, 95% CrI: 0.72-0.81), drinking (OR = 0.29, 95% CrI: 0.21-0.39), and rumen temperature (-0.28°C, 95% CrI: -0.30 to -0.27) decreased relative to Reference herds. However, daily time budgets for lying, ruminating, and grazing remained similar across herds. While lower in magnitude, rumen temperature and hourly behavioral changes were also noted during non-visit hours, suggesting carry-over benefits beyond discrete visits. Despite minimal effects on daily behavioral time budgets, treed area access reduced rumen temperature, and provided opportunities for choice expression. This proof-of-concept study demonstrates that voluntary access to treed areas is feasible which could be implemented with remanent tree stands; such access is valued by cows for both thermal relief and non-thermal benefits, offering potential for enhancing agency in pastoral dairy systems.

The objective of this study was to characterize cow- and herd-level patterns of somatic cell counts (SCC) in organic-certified cows enrolled in the DHI program, considering cow (parity, DIM, milk yield, and breed), herd (herd size), and environmental factors (geographic region, year, and season). The data set comprised 2,327,479 test-day records collected between 2018 and 2025 from 430 organic-certified dairy farms enrolled in the DHI program through the Dairy Records Management Systems, representing a total of 364,413 lactations. To evaluate potential associations at the cow-level between SCC and the variables of interest, separate linear mixed models were fitted for interactions between pairs of explanatory variables using natural log-transformed SCC (LnSCC). Additionally, relative frequencies of observations across SCC categories (≤100,000, 101,000-200,000, 201,000-500,000, 501,000-1,000,000, and >1,000,000 cells/mL) were calculated for each level of the categorical variables evaluated. For the herd-level analysis, mean herd SCC was calculated for each herd-year-season combination, and relative frequencies across SCC categories were estimated. Cumulative link mixed models for ordinal outcomes were used to assess herd-level associations between variables of interest and SCC categories, by calculating the probabilities of herds falling into higher ordinal SCC categories across explanatory variable levels. The cow-level results were back-transformed to the original SCC scale for presentation purposes, indicating that SCC increased with parity and varied throughout the lactation, peaking in early lactation (0-30 DIM), decreasing during mid-lactation (31-100 DIM), and gradually increasing again toward late lactation. Cows in the lowest quartile of relative milk yield consistently exhibited higher SCC across DIM categories compared with cows in the higher quartiles of MY. Holsteins had the lowest SCC, whereas Jersey and other breeds had higher values. Seasonal effects were evident, with SCC peaking during summer, particularly from July to September, and cows in the Midwest showing lower SCC than those in the Northeast, South, and West. SCC were highest in large herds (>500 cows) and lowest in medium-sized herds (101-500 cows). Similarly, the proportion of cows in the lowest SCC category (<100,000 cells/mL) decreased with increasing parity and was lower during early and late lactation and during the summer months. Holsteins had the highest proportion of cows in the lowest SCC category. Larger herds and farms located in the South and West showed greater proportions of cows in SCC categories above 200,000 cells/mL. Over the last 3 years of the study period, the proportion of observations in SCC >200,000 cells/mL increased in large herds and on farms in the South and West but declined in medium-sized herds (101-500 cows). At the herd-level analysis, larger herds and farms located in the South had a greater probability of being classified into higher SCC categories than smaller herds and farms located in the other 3 regions, respectively. Additionally, the probability of higher SCC categories was greater during the hot season than during the cold season. Overall, multiple variables were associated with the cow- and herd-level patterns of SCC in US organic-certified dairies, reflecting the combined effects of cow physiology, herd characteristics, seasonal patterns, and regional environmental conditions.

Subclinical mastitis persists as a challenge in dairy production, contributing to significant economic losses, compromising animal health and welfare, and driving antimicrobial use. It adversely affects milk quality, farm productivity, and overall profitability. This narrative review synthesizes historical literature, knowledge, and tools for herd-level udder health monitoring, with a focus on indices derived from repeated individual cow SCC measurements. Grounded in epidemiological principles, this review is structured around the life cycle of dairy cattle, using SCC data collected through routine milk recording tests to support meaningful interpretation of udder health dynamics across different physiological stages, not solely the lactation period. While SCC measurements are exclusively obtained during lactation, they may also be used to infer udder health status and dynamics around nonlactating periods; however, this approach may not fully represent the entire nonlactating stage or capture infectious events occurring between widely spaced tests or long before a cow's first SCC measurement. This framework also acknowledges that udder health is influenced by age, parity, and physiological and production stages, and that effective monitoring requires thoughtful interpretation of available data across the entire lactational trajectory. It supports more comprehensive and sustainable udder health herd-level management strategies. The review presents key herd-level udder health indices, discusses considerations for their use, and highlights the importance of standardized definitions and thresholds to ensure consistency and comparability. It also provides a curated selection of indices, including definitions, calculation methods, strengths and limitations, and reference values reported in the literature. This review aims to support veterinarians and dairy producers who routinely use summarized SCC reports generated through milk recording systems in implementing robust mastitis monitoring strategies throughout the cow's life cycle. The objective is to provide conceptual guidance and practical considerations that can be applied across a wide range of dairy production systems and herd sizes.

Individual animals can differ considerably in how they feed, drink, and compete for resources, yet much data analysis still relies on group-level comparisons that obscure these individual differences. Electronic feeding and drinking systems make it possible to characterize individual behavioral profiles within groups. Using 107 lactating Holstein dairy cows tracked over 207 d, we extracted 16 behavioral variables from electronic feed bin and water bin data, capturing conventional metrics (feeding and drinking intake, duration and meal frequency) alongside measures of non-nutritive visits, social competition (replacement events), and indicators of feed quality (e.g., proportion of fresh feed remaining upon arrival). Bayesian mixed-effects models quantified repeatability (between-individual variation in average behavioral expression) and predictability (between-individual variation in within-individual consistency). Variables capturing non-nutritive visits, social competition, and drinking duration showed the greatest and most consistent among-individual variation, while daily feed intake was among the least discriminating, suggesting individuals converge to similar intakes through different strategies. To identify behavioral profiles, we applied principal component analysis with varimax rotation to the 8 most repeatable and individually variable behavioral measures, then used k-means clustering on the rotated principal components. This yielded 4 distinct profiles: "frequently replaced" cows (the majority of the herd, frequently replaced at the bins), "contest-winning" cows (initiating many replacements with efficient, uninterrupted meals), "frequent drinker visitors" (many long drinking visits spread across the day), and "fragmented feeders" (many short, interrupted visits with frequent replacement events). These results illustrate how data streams from electronic feeders and drinkers can be used to build individual behavioral profiles that would not be apparent using generic group-level analyses. This framework may help researchers identify cows most susceptible to negative impacts when housed in competitive environments. To facilitate access across species and systems we developed moo4feed (https://www.skysheng.io/moo4feed/), an open-source R package designed to extract individual behavioral variables from electronic feeder and drinker data.

Salmonella Dublin, a cattle-adapted serovar of Salmonella enterica ssp. enterica with zoonotic potential, has become a pathogen of increasing concern for the dairy industry in Canada and beyond. A comprehensive understanding of its epidemiology is crucial to guide effective surveillance and control. The objectives of this serial cross-sectional study were to estimate the true herd-level seroprevalence of Salmonella Dublin and to characterize the spatial distribution of Salmonella Dublin-seropositive dairy herds in Alberta, Canada. Bulk tank milk (BTM) samples were collected from all active dairy herds in Alberta, Canada, in June (n = 462) and December (n = 451) 2024, and PrioCHECK ELISA was used to detect antibodies against Salmonella Dublin. Herds were classified as positive if ≥ 1 sample had a percent positivity ≥ 35. True seroprevalence was estimated using a Bayesian latent class model accounting for imperfect sensitivity and specificity. Spatial patterns were evaluated using a Bayesian geostatistical model, and a spatial scan statistic was used to detect localized clusters. The estimated true prevalence of Salmonella Dublin-seropositive herds in Alberta was 14.9% (95% Bayesian credible interval: 7.3-28.2%), with regional estimates of 8.0% (95% BCI = 1.6-22.6%), 13.9% (95% BCI = 4.2-31.8%), and 20.9% (95% BCI = 8.5-42.5%) for the north, central, and south regions of Alberta, respectively. The continuous spatial risk surface revealed that the true herd seropositivity varied markedly across Alberta, with some areas having much higher predicted seropositivity probabilities than others. Furthermore, 2 localized clusters of higher seropositivity were detected: a prominent cluster (95-km radius) in southwestern Alberta and a relatively smaller cluster (19-km radius) in a high-density dairy corridor in the central region. These findings indicate that Salmonella Dublin exposure is moderate in Alberta, with marked regional heterogeneity and pronounced spatial gradients in herd-level seropositivity. Incorporating spatial context into surveillance and control may improve targeting of interventions aimed at reducing within-region transmission. These findings also illustrate the value of Bayesian latent class modeling for generating bias-adjusted true seroprevalence estimates in the absence of a gold-standard diagnostic test.

Calf weaning operations represent a specialized segment of beef production in Southern Germany which manage the critical transition period from milk feeding to complete weaning. These farms face challenges comparable to those encountered by veal and beef enterprises in establishing optimal housing and management conditions that ensure both animal welfare and economic viability. The present explorative study aimed to identify management-, housing-, and environment-related risk factors associated with antimicrobial treatment incidence (TI), average daily gain (ADG), and mortality in 53 Bavarian calf weaning operations. Data sources included: (1) a structured questionnaire covering calf purchase, arrival management, feeding, housing, treatment protocols, and prophylaxis; (2) antimicrobial usage and growth performance records; and (3) standardized on-farm assessments of housing conditions and clinical examinations of 1,060 calves. Median TI was 14.0, median ADG 1,121g/day, and median mortality 1.0%. Higher TI was significantly (P < 0.05) associated with a higher number of fattened calves per year, shared utensils between calf groups, and the presence of moderately impaired subjective air quality, whereas higher relative humidity was associated with decreased TI. Implementation of an all-in/all-out system was associated with lower mortality. Higher ADG was associated with larger herd size and the absence of a bedded lying area, whereas poor hygiene was associated with lower ADG. These findings provide a basis for future prospective studies and evidence-based recommendations aimed at optimizing housing and management practices to improve animal welfare, reduce antimicrobial use, and enhance economic performance in these specialized calf weaning operations.

Bovine leukemia virus (BLV) infection in calves may contribute to early dissemination within dairy herds. This study aimed to determine the BLV infection prevalence in pre-colostral and neonatal calves and its association with management-related factors in dairy farms in Uruguay. Two studies were conducted. Study 1 was a retrospective analysis of archived pre-colostral blood samples from 75 calves from one farm. Samples were analyzed by quantitative real-time PCR (qPCR) and ELISA, and previous ELISA and qPCR results from dams of calves positive by qPCR and/or ELISA were reviewed. Study 2 was a cross-sectional study of blood samples from 542 neonatal calves aged 1-30 days from 30 dairy farms, analyzed by qPCR, with management data collected by questionnaire. In Study 1, 6.7% (5/75) of calves were qPCR-positive, and 4.0% (3/75) were ELISA-positive; one calf was positive by both assays. All seven dams of calves positive by qPCR and/or ELISA were ELISA-positive, while five were also qPCR-positive. In Study 2, 8.9% (48/542; farm-level bootstrap 95% CI 3.7-15.1%) of calves were qPCR-positive, within-herd apparent prevalence ranged from 0% to 54.5%, and 43.3% (13/30) of farms had ≥1 qPCR-positive calf. In Study 1, qPCR positivity before colostrum ingestion was consistent with prenatal transmission. Exploratory multivariable analysis suggested possible farm-level associations between herd size, maternal vaccination against neonatal calf diarrhea, rotation of calf-rearing areas, and type of liquid feed and qPCR-positive calves. These findings suggest that BLV infection can be detected during the neonatal period and support investigation of management and biosecurity practices.

Foot-and-mouth disease (FMD) virus is one of the most feared and most consequential pathogens of livestock worldwide. It can be spread rapidly by the transboundary movement of animals, animal products, and by-products. In January 2025, Germany detected its first FMD outbreak since 1988 in extensively reared water buffalo on a small farm in the state of Brandenburg, directly outside Berlin, the federal capital. Immediate control measures including a standstill for movements of susceptible animals and pre-emptive culling were implemented by the veterinary authorities. Whole-genome sequencing identified the virus as serotype O, topotype ME-SA, lineage SA-2018 and revealed extensive recombination, but cross-neutralization assays suggested good heterologous protection by an O/PanAsia-2 vaccine strain. Epidemiological back-calculation placed the time of virus introduction in late December 2024. Although the entry route remains unresolved, human-associated introduction is most likely. Network analysis revealed minimal farm connectivity, and simulations predicted low potential for onward transmission, which is consistent with the outbreak being ultimately restricted to a single herd. This event underscores the constant and unpredictable risk of introduction of the virus. Early detection through increased awareness and comprehensive differential diagnostics as well as the international collaboration of veterinary services, laboratories, and experts are essential in the face of the global presence of FMD.

Reducing methane emissions from dairy cattle has gained considerable attention due to its dual benefits of improving feed efficiency and mitigating climate change. Consequently, phenotyping methane emissions in dairy populations has become increasingly important to enable direct genomic selection for lower methane emissions in breeding programs. Sniffer devices are receiving growing attention and are currently being deployed on commercial farms. However, these devices do not measure airflow and therefore provide methane concentration measurements rather than direct estimates of methane production. In this study, a new method is proposed to estimate individual cow methane production from sniffer device data that does not rely on regression on production traits and can therefore be classified as a Tier 3 approach. This novel methane production trait was derived using sniffer measurements collected in two dairy cattle populations: Spain (n = 1576) and The Netherlands (n = 2470). The proposed trait was compared with two alternative methane production estimates derived from production traits, representing a Tier 2 and an existing Tier 3 method. Phenotypic correlations between the Tier 3 traits were high (R > 0.90), whereas correlations between the Tier 2 and Tier 3 methods were substantially lower, ranging from 0.04 to 0.44. Strong agreement was observed between herd-level averages of the Tier 3 traits, while discrepancies between Tier 2 and Tier 3 estimates were more pronounced. Overall, the Tier 2 equation yielded higher methane production estimates than those obtained from sniffer-based Tier 3 traits. Heritability estimates for the Tier 3 traits ranged from 0.06 to 0.13, whereas a higher heritability (0.18-0.22) was observed for the Tier 2 trait, with standard errors between 0.02 and 0.03. Repeatability estimates were greater for the Tier 3 traits, with values ranging from 0.54 to 0.58 in Spain and from 0.25 to 0.29 in The Netherlands. The Tier 2 trait also exhibited a high repeatability (0.55-0.80). We propose this new sniffer-based Tier 3 trait as an alternative methane production phenotype that is not derived from individual production traits, thereby reducing the risk of spurious associations between methane emissions and yield-related traits. The proposed phenotype showed strong agreement with previously used Tier 3 traits and exhibited comparable heritability estimates. Nevertheless, several limitations must be acknowledged. In particular, this trait provides an estimate of methane production rather than a direct measurement, as current sniffer devices cannot capture the complete expiration or eructation plume. Despite these limitations, the trait enables the estimation of genetic trends and the prediction of breeding values expressed in biologically meaningful units. As such, it represents a valuable tool for supporting mitigation strategies and informing breeding policies aimed at reducing methane emissions from dairy cattle.

The success of stallion semen cryopreservation is limited by substantial variation among stallions and by temporal variation within individual donors. However, the equine breeding industry requires predictable, stable, and efficient cryopreservation protocols to support the increasing use and dissemination of valuable genetics. One possible strategy for improving semen freezing is to introduce a preconditioning step before cryopreservation to prepare spermatozoa for the unavoidable stresses associated with freezing and thawing. This study evaluated the effects of mild hydrostatic pressure preconditioning on semen samples from Arabian and Shagya-Arabian stallions. Sixty-three semen samples from ten stallions were included in the study, spanning between July and April, in 31 collection days. Before routine cryopreservation, each sample was split into one control and six treatment aliquots, subjected to one of six hydrostatic pressure preconditioning treatments or maintained as control. After freezing and thawing, total motility (TM) and progressive motility (PM) were assessed using computer-assisted sperm analyser. Five of the six preconditioning treatments significantly improved both TM and PM compared with the control (p < 0.05). TM increased from 51.87% in control samples to 56.39-59.17% in mild-hydrostatic-pressure-treated samples, while PM increased from 39.56% to 43.81-47.00%. In our study, mild hydrostatic pressure preconditioning was readily integrated into the routine semen cryopreservation workflow and improved post-thaw motility. These findings indicate improved motility-based cryosurvival of stallion spermatozoa; however, the study did not assess pregnancy rate, foaling rate, or other in vivo fertility outcomes. Artificial insemination trials are therefore required before conclusions can be drawn regarding reproductive performance.