The influence of cow factors on the incidence of clinical mastitis in dairy cows

Factors influencing somatic cell count and leukocyte composition in cow milk: a field study

In recent years, there has been a proliferation of studies investigating the composition of somatic cell count (SCC) of milk, focusing on neutrophils (NEU), lymphocytes (LYM), and macrophages (MAC). These 3 components are indeed crucial for the animal's immune response to mastitis-causing pathogens. The study examined various factors influencing somatic cell count and leucocyte components in cow milk, including lactation stage, parity, and milk electrical conductivity, using data from 179 dairy cows across 6 farms throughout the entire lactation. Statistical analyses, including mixed models and logistic regression, were employed to investigate the relationships between these variables and identify risk factors for high SCC levels. Results showed that factors such as parity and lactation stage were significantly associated with somatic cell composition. In particular, the highest milk NEU values (>60% of the total leucocytic fraction) and lowest MAC values (<20%) were found at the beginning and the end of lactation, that are the critical periods for udder health. High milk electrical conductivity, low milk production, number of parity, and poor hygiene scores were identified as contributing to increased SCC. Additionally, elevated percentages of NEU and LYM in milk were associated with increased risk of high SCC values, indicating potential udder health issues.

An observational study to investigate the association of teat skin condition with clinical mastitis risk

The importance of teat canal integrity and its adjacent tissues in the dynamics of IMI is well documented, whereas research on the relationship between teat skin condition and clinical mastitis occurrence is scarce. The objective of this prospective cohort study was to investigate the association of teat skin condition with clinical mastitis occurrence in a closed cohort from a commercial dairy farm with a thrice daily milking schedule in the Northeast United States. We tested the hypothesis that quarters with teats with altered skin condition would have higher odds of clinical mastitis than those with normal skin. Teat skin condition from 2,670 cows was assessed during a single visit and categorized into (1) normal, (2) dry skin, (3) skin lesion, and (4) dry skin and skin lesion. Cows were monitored for 2 wk after the teat skin condition assessment, and the occurrence of clinical mastitis at the quarter level was documented. A generalized linear mixed model with a logit link and a binomial distribution revealed an association between teat skin condition and the occurrence of clinical mastitis. Compared with quarters with teats with normal teat skin, the odds (95% CI) of clinical mastitis were 0.98 (0.60-1.60) for teats with dry skin, 1.88 (0.97-3.66) for teats with a skin lesion, and 4.87 (1.71-13.85) for teats with dry skin and a skin lesion. We conclude that quarters from teats with dry skin and skin lesions had higher odds of clinical mastitis. In addition, we found evidence that quarters with teats with skin lesions have higher odds of clinical mastitis than those with normal teat skin, though future studies are needed. The results from this study show that teat skin condition should be considered in mastitis control programs on dairy operations.

Effects of extending dairy cow longevity by adjusted reproduction management decisions on partial net return and greenhouse gas emissions: A dynamic stochastic herd simulation study

Prolonging dairy cattle longevity is regarded as one of the options to contribute to more sustainable milk production. Because failure to conceive is one of the main reasons for culling, this study investigates how adjustments in reproduction management affect partial net return at herd level and greenhouse gas emissions per unit of milk, using a dynamic stochastic simulation model. The effects of reproduction decisions that extend cattle longevity on milk yield, calving interval and pregnancy rate were derived from actual performance of Dutch commercial dairy cows over multiple lactations. The model simulated lactations, calving, and health status events of individual cows for herds of 100 cows. Scenarios evaluated differed in the maximum number of consecutive AI attempts (4, 5, or 6 services), or the production threshold (20, 15, or 10 kg of milk/d) at which cows that failed to conceive are culled (reproductive culling). Annual partial net return was computed from revenues of sold milk, calves, and slaughtered cows, and the costs from feed consumption, rearing replacement heifers, AI services, and treatment for clinical mastitis and lameness. Greenhouse gas emissions were computed for feed production, enteric fermentation, and manure management, and were expressed as total CO2 equivalents (CO2-eq). Average age at culling increased with an increased maximum number of AI services. This increase was larger when going from a maximum of 4 to 5 AI attempts (108 d) than from a maximum of 5 to 6 attempts (47 d). Similarly, the average age at culling increased from 1,968 to 2,040 and 2,132 d when the threshold for reproductive culling decreased from 20, to 15 and 10 kg of milk/d, respectively. Average annual partial net return increased by 1.1% from €165,850 per 100 cows at a maximum of 4 AI to €167,670 per 100 cows at a maximum of 6 AI, and increased by 4.3% from €161,210 per 100 cows at a reproductive culling threshold of 10 kg/d to €168,190 per 100 cows at a threshold of 20 kg/d. Greenhouse gas emissions decreased by 1.2% from 0.926 to 0.915 kg CO2-eq per kg of fat- and protein-corrected milk (FPCM) with an increase in a maximum number of AI from 4 to 6 AI. Conversely, greenhouse gas emissions increased by 0.2% from 0.926 kg at a threshold of reproductive culling of 20 kg/d to 0.928 kg CO2-eq/kg FPCM at a threshold of 10 kg/d. Although lowering the threshold for reproductive culling has the potential to extend cattle longevity more than increasing the maximum number of AI services, only the increase in AI services benefits a farm's partial net return, while reducing greenhouse gas emissions.

Association between non-esterified fatty acids and calcium concentrations at calving with early lactation clinical diseases, fertility and culling in grazing dairy cows in Uruguay

This study describes the association of non-esterified fatty acids (NEFA) and calcium concentrations at calving with early lactation disease, reproductive performance and culling in 646 dairy cows from 13 commercial grazing dairy herds in Uruguay. During one year, health events were recorded from calving to 30 days in milk (DIM). The first author visited each farm every 20 days. During each visit, body condition score (BCS) was recorded (scale 1-5), defining BCS < 3 as suboptimal and BCS > 3 as optimal, and a blood sample was taken from cows between 0 and 4 DIM for metabolite determination. To evaluate the association between health events (i.e., retained placenta-metritis and clinical mastitis) and risk factors (parity, BCS, high NEFA (> 0.6 mmol/L) and subclinical hypocalcemia (SCH) (< 2.10 mM)) data were analysed using multivariable logistic regression models. To evaluate the association of health events and risk factors with reproductive performance and culling, data were analysed using Cox proportional hazard regression models. A risk factor and an outcome of interest were assumed to be associated at P < 0.05 and a tendency to be associated was defined at P < 0.10. Overall, 47 % (n = 303) of the cows showed elevated NEFA concentration and 77 % (n = 499) had SCH. In addition, 21.5 % (n = 139) of the cows recorded at least one clinical disease. Cumulative incidence was 17 % (n = 109) for clinical mastitis, 4.2 % (n = 27) for retained placenta (RP)-metritis and 1.4 % (n = 7) for lameness. Clinical mastitis was associated with parity, with lower odds in primiparous (PP) cows (OR = 0.42, P < 0.01). Cows in an optimal BCS also tended to have lower odds (OR = 0.66, P = 0.07). Moreover, high NEFA and SCH cows had higher odds of CM (OR = 4.5, P = 0.01 and OR = 1.75, P = 0.04, respectively). Retained placenta-metritis tended to be associated with high NEFA concentration (OR = 2.2, P = 0.06). Primiparous cows with suboptimal BCS showed an increased first insemination rate (HR = 2.34; P < 0.01). The risk of culling was lower in PP cows (HR = 0.19; P < 0.01) and in cows with optimal BCS and low NEFA concentration (HR = 0.38; P = 0.03). Our data show that metabolic challenge (defined as peripartum suboptimal BCS, high NEFA or SCH) is associated with increased odds of clinical mastitis and RP-metritis, decreased probability of insemination and increased hazard of culling. Under grazing conditions, we suggest that farm management to improve the metabolic adaptation to lactation represents an opportunity to enhance cow performance in terms of health, fertility and longevity.

Body conformation traits in early-lactation associated with clinical mastitis and lameness in lactating Chinese holstein cows

BACKGROUND

Comprehending the correlation between body conformation traits of cows at the early stages of lactation and prevalent lactation diseases might facilitate the execution of selection and feeding strategies that prioritize cow health. This study aimed to evaluate the impact of body conformation traits on the incidence of clinical mastitis and lameness in Chinese Holstein cows. From a pasture herd of 1472 early lactating Chinese Holstein cows, we evaluated 20 body conformation traits. During lactation, this pasture herd was visited weekly to gather clinical mastitis and lameness data. A nine-point scale was used to determine the conformation traits of cows to clarify their linear characters, including frame capacity, rump (RU), feet and leg (FL), mammary system (MS), and dairy character. A longitudinal binary disease (0 = healthy; 1 = diseased) data structure was created by allocating disease records to adjacent official test dates. The impact of body conformation traits on the risk of developing diseases (clinical mastitis and lameness) was analyzed using the logistic regression models.

RESULTS

Compared to cows with low total scores (75-79 points), those with high total scores (80-85 points) of body conformation traits had a significantly lower risk of mastitis (P < 0.001). The disease status (0 or 1: binary variable) of clinical mastitis in lactating cows was significantly impacted negatively by age (P < 0.05). The fore udder attachment (FUA), angularity, rear attachment height (RAH), and rear teat placement (RTP) were all significantly associated with clinical mastitis during lactation (P < 0.05). The rear leg-rear view (RLRV) was significantly correlated with correlated considerably (P < 0.05) with lameness during lactation. An ideal score of four points on the lameness risk dimension of the RLRV may indicate a low risk of lameness. Since the risk of mastitis decreased as this trait score increased, the RTP may be an ideal marker for mastitis risk.

CONCLUSIONS

According to the study, clinical mastitis and lameness risks in cows can be estimated using their body conformation traits. Cows with more centrally located rear teats have a lower risk of mastitis. These results may help dairy farmers identify cows at high risk of disease early in lactation and aid in breeding for disease resistance in cows.

Breed and non-genetic risk factors associated with the prevalence of subclinical mastitis in livestock systems of Arauca, Colombian orinoquia

Subclinical Mastitis (SCM) is caused by several factors associated with the interaction of the individual cow, cow management, and the environment. The aim of this study was to assess the breed and non-genetic risk factors on the prevalence of SCM in cows from the dual-purpose livestock system on the floodplain of Arauca, Colombian Orinoquia. Milk samples were taken from the individual mammary quarters of 481 cows representing 28 different farms where the electrical conductivity (EC) test applied. To determine the factors associated with SCM, a multiple logistic regression analysis was used. The response variable was the SCM presence (1), or absence (0) obtained with the EC test. Breed was included as a genetic risk factor, and as non- genetic risk factors: number of cows in production, daily milk production, lactation month, cow age, climatic period, body condition, and calving number. The factors that were significantly associated with the SCM presence were body condition, climatic period, and breed (p < 0.05). Odds ratio (OR) analysis of significant effects indicates that for each unit increase in body condition, the OR of having animals with SCM is reduced by 71%. In the dry period the OR of animals with SCM increases by 150% compared to the rainy period. Composite breeds reduce the OR of SCM animals by 73%, compared with Indicus-predominance animals. In this study, the occurrence of SCM in extensive management systems in Arauca, Colombian Orinoquia, is determined by the risk factors of breed, climatic period, and body condition.

Environmental and Breed Risk Factors Associated with the Prevalence of Subclinical Mastitis in Dual-Purpose Livestock Systems in the Arauca Floodplain Savannah, Colombian Orinoquia

The aim of this study was to assess the environmental and breed risk factors associated with the prevalence of subclinical mastitis (SCM) in cows in the dual-purpose livestock system of Arauca, Colombian Orinoquia. Milk samples were taken from 1924 mammary quarters, corresponding to 481 cows on 28 different farms, and the California Mastitis Test (CMT) was applied. Risk factors associated with SCM were determined using multiple logistic regression analysis. The response variable was the presence (1) or absence (0) of SCM. Breed was included as a genetic risk factor, and daily milk production, number of cows in production, lactation month, calving number, cow age, climatic period, and body condition were included as environmental risk factors. The analysis of the odds ratio (OR) of significant effects indicated that the factors significantly associated with the presence of SCM were the number of cows (OR = 2.29; p = 0.005), milk production (OR = 0.88; p = 0.045), and the Taurus-Indicus breeds (OR = 1.79; p = 0.009) and composite breed (OR = 3.95; p = 0.005). In this study, the occurrence of SCM was determined by the following risk factors: number of cows, milk production, and breed. Likewise, the highest prevalence seemed to occur on farms with less technological development and sanitary management of producers from the lowest socioeconomic stratum.

Incidence rate, risk factors, and bacterial causes of clinical mastitis on dairy farms in Hawassa City, southern Ethiopia

Mastitis is the most common disease of dairy cattle worldwide, causing economic losses due to reduced yield and poor quality of milk. It is of particular concern in Ethiopia, where effective prevention and control practices are lacking. The objective of the present prospective longitudinal study was to estimate the incidence rate of clinical mastitis (CM), identify the risk factors, isolate the bacterial agents, and determine the risk of recurrence. For this purpose, a total of 217 lactating cows were followed up every two weeks from calving to drying off or the end of the study period. Of these, 79 (36.41%) developed CM, of which 23% had recurrent infections in the same or a different quarter. The overall incidence rate of CM was 83.72 (95% CI: 63.2-98.2) cases per 100 cow-years at risk. In the multivariable Cox regression model, the risk of CM was found to be significantly higher in multiparous cows (HR = 1.96; p = 0.03), in cows with a history of mastitis (HR = 2.04; p = 0.030), in cows that had severely keratinized teat end condition (HR = 7.72; p < 0.001) and in cows kept in poorly cleaned barns (HR = 1.89; p = 0.007). The pathogenic bacteria isolated from mastitis-positive cows were Staphylococcus aureus (28.1%), E. coli (21.1%), Bacillus spp. (14%), Streptococcus spp. (14%), coagulase-negative staphylococci (12.3%), non aureus staphylococci (5.3%), Enterobacter spp. (3.5%), Klebsiella spp. (1.8%), Corynebacterium spp. (1.8%), and Proteus spp. (1.8%). The high incidence rate of CM in the present study shows that the disease spreads rapidly and can be responsible for a significant economic loss to milk producers in the study area. Therefore, raising awareness among dairy farmers, early detection and treatment of cases, post-milking teat disinfection, improvement of the hygienic status of cows and barns, use of dry cow therapy, and culling of chronic cases are recommended as viable measures to prevent and control clinical mastitis in the study area.

Prevalence and risk factors of Klebsiella spp. in milk samples from dairy cows with mastitis-A global systematic review

Introduction

The overall prevalence of Klebsiella spp., a group of important zoonotic pathogens, in the global dairy herds and the risk of cross-species transmission between humans and dairy cows remain to be clarified. This systematic review aimed to determine the prevalence of Klebsiella spp. in milk samples from dairy cows with mastitis worldwide and to assess the factors influencing the prevalence of these strains.

Methods

Qualified studies published from 2007 to 2021 were retrieved from ScienceDirect, Web of Science, PubMed, WanFang Database, China National Knowledge Infrastructure (CNKI), and VIP Chinese Journal Database. Calculations of prevalence and their 95% confidence intervals (CIs) were performed for all the studies using the Freeman-Tukey double arcsine transformation (PFT).

Results

A total of 79,852 milk samples from 55 manuscripts were examined in this meta-analysis, and 2,478 samples were found to be positive for Klebsiella spp. The pooled prevalence estimates worldwide were 7.95% (95% CI: 6.07%-10.06%), with significant heterogeneity (I 2 = 98.8%, p = 0). The sampling period of 2013-2020 had a higher (p < 0.05) Klebsiella-positive proportion of milk samples (12.16%, 95% CI: 8.08%-16.90%) than that of 2007-2012 (3.85%, 95% CI: 2.67%-5.21%), indicating that bovine mastitis caused by Klebsiella may become increasingly prevalent. The risk factors for the high prevalence of Klebsiella in milk samples mainly included: economic development level (developing countries; 11.76%, 95% CI: 8.25%-15.77%), mastitis type (CM; 11.99%, 95% CI: 8.62%-15.79%), and population density (>500 per sq km; 10.28%, 95% CI: 2.73%-21.58%). Additionally, a bivariate meta-regression analysis revealed that the multidrug-resistance (MDR) rate of the epidemic strains was also closely related to economic development level (R 2 = 78.87%) and population density (R 2 = 87.51%).

Discussion

Due to the potential risk of cross-species transmission between humans and cows, the prevalence of mastitis milk-derived Klebsiella and its high MDR rate need to be monitored, especially in developing countries with high population densities.

Estimates of dairy herd health indicators of mastitis, ketosis, inter-calving interval, and fresh cow replacement in the Piedmont region, Italy

Test-day milk analysis has largely been used to study health and performance parameters in dairy cows. In this study, we estimated four health indicators of dairy cows using test-day data. Our purpose was to estimate (1) mastitis incidence rate, prevalence, and the probability of recovery; (2) the incidence proportion of ketosis; (3) the duration of inter-calving interval; and (4) the risk of a fresh cow being replaced, in a large cohort of dairy herds in the Piedmont region (Italy). We retrospectively analysed test day records of 261,121 lactating cows and 1315 herds during five years (2015-2020). Mastitis was defined by somatic cell count and ketosis by fat-to-protein ratio. Calving dates were used to calculate ICI and to estimate the removal of a fresh cow from the herd. Mixed-effect generalized linear models were used to adjust for unmeasured herd-level risk factors. The risk of mastitis increased by 120% with parity (Odds ratio [OR] = 2.20, confidence interval [CI]: 2.17 - 2.23), by 7% by months in milking (OR = 1.07, CI: 1.07 - 1.07), and even more if the cow was already affected during the same lactation (OR = 8.74, CI: 8.67 - 8.82). Lactose concentration on the previous test day was the best positive prognostic factor for mastitis recovery (OR = 1.12, CI: 1.08 - 1.17). Ketosis risk was the highest between 3rd and 4th lactations and itself increased the risk of having ICI longer than 440 days (OR = 1.12, CI: 1.02 - 1.22), and fresh-cow removal (OR = 1.75, CI: 1.58 - 1.93). Also, the removal of fresh cows was more likely when mastitis (OR = 1.31, CI: 1.19 - 1.45) or long ICI (OR = 1.34, CI: 1.22 - 1.48) occurred. For each health indicator, herd-level risk factors had an important role (18-56% of within-herd covariance). Our results indicate that milk analysis could be also useful for predicting mastitis, its cure rate, and ketosis. Cow-level risk factors are not enough to explain the risk of these issues. By studying a large population over a long period, this study provides an updated estimate of dairy cow health indicators in Piedmont (north-western Italy), useful for benchmarking dairy herds.

Prevalence and risk factors of coliform-associated mastitis and antibiotic resistance of coliforms from lactating dairy cows in North West Cameroon

Background

Coliform bacteria are major causative agents of bovine mastitis, a disease that has devastating effect on dairy animal health and milk production. This cross-sectional study, carried out in the North West region of Cameroon, sought to determine the prevalence of bovine mastitis, coliforms associated with bovine mastitis, risk factors for infection and the antibiotic resistance pattern of coliform bacterial isolates.

Materials and methods

A total of 1608 udder quarters were sampled from 411 cows using a questionnaire, clinical examination, California Mastitis Test and milk culture. Primary isolation of coliform bacteria was done on MacConkey agar while identification of coliforms employed Gram-staining and biochemical testing. Each coliform bacterial isolate was challenged with 11 antibiotics using the Kirby-Bauer disc diffusion method.

Results

The prevalence of mastitis was 53.0% (218/411) and 33.1% (532/1608) at the cow- and quarter-levels respectively. Overall, 21.9% (90/411) cows and 8.2% (132/1608) udder quarters showed coliform mastitis. Escherichia coli was isolated in 7.0% of mastitis milk, and other coliforms isolated were Enterobacter cloacae (12.6%), Klebsiella pneumoniae (2.4%), Enterobacter sakazakii (1.1%), Klebsiella oxytoca (0.8%), Citrobacter freudii (0.4%), Serratia ficaria (0.4%) and Serratia liquefaciens (0.2%). Lactation stage, breed, history of mastitis and moist/muddy faeces contaminated environment were significantly associated (P-value < 0.05) with coliform mastitis. Coliform isolates (99.0%; 203/205) were resistant to at least one antibiotic tested. Amoxicillin had the highest resistance (88.8%) while norfloxacin had the least resistance (3.4%). Multidrug resistance was exhibited by 52.7% (108/205) of the isolates in a proportion of 27.8% Enterobacter cloacae, 10.7% E. coli, 6.3% Klebsiella pneumoniae, 2.9% Enterobacter sakazakii, 2.0% Klebsiella oxytoca, 1.0% Citrobacter freundii, 1.0% Serratia ficaria, 0.5% Serratia liquefaciens and 0.5% Serratia odorifera.

Conclusion

Results indicate a need to educate these dairy farmers about mastitis (particularly subclinical), proper hygiene methods in milking and the public health implications of consuming contaminated raw milk.

Prediction of Acute and Chronic Mastitis in Dairy Cows Based on Somatic Cell Score and Mid-Infrared Spectroscopy of Milk

Simple Summary

Mid-infrared (MIR) spectroscopy is the method of choice to determine milk components like fat, protein and urea. We examined the potential of MIR spectra analyses for the prediction of clinical mastitis events of dairy cows additionally, or alternatively, to somatic cell count, which is routinely used as an indicator for mastitis monitoring. Prediction models based on MIR spectra and a somatic cell count-derived score (SCS) were developed and compared. A model based on MIR spectra and SCS proved more accurate at predicting mastitis than models based on either indicator alone. Consequently, MIR spectra analyses add extra value in the prediction of clinical mastitis, making them potentially useful for dairy farm management and as an auxiliary trait for the genetic evaluation of udder health.

Abstract

Monitoring for mastitis on dairy farms is of particular importance, as it is one of the most prevalent bovine diseases. A commonly used indicator for mastitis monitoring is somatic cell count. A supplementary tool to predict mastitis risk may be mid-infrared (MIR) spectroscopy of milk. Because bovine health status can affect milk composition, this technique is already routinely used to determine standard milk components. The aim of the present study was to compare the performance of models to predict clinical mastitis based on MIR spectral data and/or somatic cell count score (SCS), and to explore differences of prediction accuracies for acute and chronic clinical mastitis diagnoses. Test-day data of the routine Austrian milk recording system and diagnosis data of its health monitoring, from 59,002 cows of the breeds Fleckvieh (dual purpose Simmental), Holstein Friesian and Brown Swiss, were used. Test-day records within 21 days before and 21 days after a mastitis diagnosis were defined as mastitis cases. Three different models (MIR, SCS, MIR + SCS) were compared, applying Partial Least Squares Discriminant Analysis. Results of external validation in the overall time window (−/+21 days) showed area under receiver operating characteristic curves (AUC) of 0.70 when based only on MIR, 0.72 when based only on SCS, and 0.76 when based on both. Considering as mastitis cases only the test-day records within 7 days after mastitis diagnosis, the corresponding areas under the curve were 0.77, 0.83 and 0.85. Hence, the model combining MIR spectral data and SCS was performing best. Mastitis probabilities derived from the prediction models are potentially valuable for routine mastitis monitoring for farmers, as well as for the genetic evaluation of the trait udder health.

Subclinical mastitis in dairy cows in south-Asian countries: a review of risk factors and etiology to prioritize control measures

Mastitis is a major production disease, causing significant economic losses for dairy farmers in South-Asian countries, as well as other parts of the world. Udder health control programs (UHCP) have been established in developed countries as an effective strategy for mastitis control but have not yet been introduced in South-Asian low-income countries like Bangladesh, India, Pakistan, and Sri Lanka. To launch UHCP successfully in dairy herds in South-Asia, it is important to know the current prevalence and risk factors for subclinical mastitis (SCM). Therefore, a narrative literature review was conducted with the aim to describe the dairy sector, the prevalence of SCM and its causal agents, risk factors for mastitis occurrence and the control measures suggested by different studies conducted in the selected countries. The literature revealed that India had the highest cattle population. Milking was mainly done by hand in all of the studied countries. Stall feeding was done in Bangladesh and Sri Lanka and limited access to grazing was also reported in some farms in India and Pakistan. There was substantial variation in the prevalence of SCM between studies in all 4 countries, ranging from about 20% to about 80%, but the average prevalence across all studies was high (50%). The most common causal agents for SCM were non-aureus staphylococci (NAS), Staphylococcus (S.) aureus, Streptococcus spp. and Escherichia (E.) coli. The management related risk factors reported for SCM were stall feeding of cows, a higher stock density, cracked floors, open drains, the presence of flies, poor drainage, peri-parturient diseases, infrequent dung removal and earth floors. The control measures suggested in these studies were to improve the hygiene and sanitation of cows, to improve the cleanliness of farms and milker's hands, to apply dry cow therapy, supplementing micronutrients and routine screening for SCM combined with taking intervention measures like isolation of cows or milking infected cows last, and proper treatment. Also, full hand milking, complete milking, machine milking, and providing feed and water immediately after milking have been recommended. Finally, we show that current literature often studies the same set of (non-manageable) risk factors, so more research is needed to obtain a comprehensive picture of the determinants of SCM. Randomized controlled trials are needed to truly quantify the effect of intervention under field conditions. Altogether, our work gives an overview of the udder health situation in South-Asia and provides the basis for the design of UHCP in this region.

First test-day postcalving risk factors for clinical mastitis in southern Chile dairy farms: A retrospective cohort study

We conducted a retrospective cohort study to evaluate risk factors associated with clinical mastitis in dairy cows in southern Chile between the first milk test after calving to 200 d in milk (DIM). Data from 8,772 cows were collected from June 2017 to November 2019 on 10 dairy farms selected by convenience in southern Chile. Data were analyzed using a multivariable mixed logistic regression using a manual backward selection process with logit link function and farm as a random effect. The dependent variable was clinical mastitis between the first milking sample collected by monthly milk sampling program up to 200 DIM. Days in milk, fat, urea, parity, season, and somatic cell counts were statistically associated with clinical mastitis in the first 200 d in milk. Cows with higher than average milk yield, parity, urea, and somatic cell count were at greater odds of being diagnosed with clinical mastitis compared with their respective referents. In contrast, higher milk fat was associated with lower odds of clinical mastitis. Significant interactions between days in milk with season and parity were observed, where for every 5-d increase in DIM, the odds of clinical mastitis decreased by different proportions depending on the interaction. Identified risk factors for clinical mastitis using first monthly milk sampling data can help dairy farmers in Chile implement herd-level mastitis prevention and control measures.

Global transcriptomic profiles of circulating leucocytes in early lactation cows with clinical or subclinical mastitis

Bovine mastitis, an inflammatory disease of the mammary gland, is classified as subclinical or clinical. Circulating neutrophils are recruited to the udder to combat infection. We compared the transcriptomic profiles in circulating leukocytes between healthy cows and those with naturally occurring subclinical or clinical mastitis. Holstein Friesian dairy cows from six farms in EU countries were recruited. Based on milk somatic cell count and clinical records, cows were classified as healthy (n = 147), subclinically (n = 45) or clinically mastitic (n = 22). Circulating leukocyte RNA was sequenced with Illumina NextSeq single end reads (30 M). Differentially expressed genes (DEGs) between the groups were identified using CLC Genomics Workbench V21, followed by GO enrichment analysis. Both subclinical and clinical mastitis caused significant changes in the leukocyte transcriptome, with more intensive changes attributed to clinical mastitis. We detected 769 DEGs between clinical and healthy groups, 258 DEGs between subclinical and healthy groups and 193 DEGs between clinical and subclinical groups. Most DEGs were associated with cell killing and immune processes. Many upregulated DEGs in clinical mastitis encoded antimicrobial peptides (AZU1, BCL3, CAMP, CATHL1, CATHL2, CATHL4,CATHL5, CATHL6, CCL1, CXCL2, CXCL13, DEFB1, DEFB10, DEFB4A, DEFB7, LCN2, PGLYRP1, PRTN3, PTX3, S100A8, S100A9, S100A12, SLC11A1, TF and LTF) which were not upregulated in subclinical mastitis. The use of transcriptomic profiles has identified a much greater up-regulation of genes encoding antimicrobial peptides in circulating leukocytes of cows with naturally occurring clinical compared with subclinical mastitis. These could play a key role in combatting disease organisms.

The Importance of Low Daily Risk for the Prediction of Treatment Events of Individual Dairy Cows with Sensor Systems

The prediction of health disorders is the goal of many sensor systems in dairy farming. Although mastitis and lameness are the most common health disorders in dairy cows, these diseases or treatments are a rare event related to a single day and cow. A number of studies already developed and evaluated models for classifying cows in need of treatment for mastitis and lameness with machine learning methods, but few have illustrated the effects of the positive predictive value (PPV) on practical application. The objective of this study was to investigate the importance of low-frequency treatments of mastitis or lameness for the applicability of these classification models in practice. Data from three German dairy farms contained animal individual sensor data (milkings, activity, feed intake) and were classified using machine learning models developed in a previous study. Subsequently, different risk criteria (previous treatments, information from milk recording, early lactation) were designed to isolate high-risk groups. Restricting selection to cows with previous mastitis or hoof treatment achieved the highest increase in PPV from 0.07 to 0.20 and 0.15, respectively. However, the known low daily risk of a treatment per cow remains the critical factor that prevents the reduction of daily false-positive alarms to a satisfactory level. Sensor systems should be seen as additional decision-support aid to the farmers’ expert knowledge.

Monitoring udder health on routinely collected census data: Evaluating the short- to mid-term consequences of implementing selective dry cow treatment

In 2013, the preventive use of antimicrobials in Dutch livestock was prohibited, including a ban on the blanket application of antimicrobial dry cow treatment (BDCT). Since then, selective dry cow treatment (SDCT) has become the standard approach. In this study, we aimed to determine the effect of the ban on BDCT and the extent of the subsequent adoption of SDCT on antimicrobial usage (AMU) and udder health on Dutch dairy farms. In the Dutch cattle health surveillance system, AMU for dry cow treatment (AMU_DCT), AMU for intramammary treatment at any point in time (AMU_IMM), and udder health indicators are routinely and continuously monitored. This provided the opportunity to study associations among SDCT, udder health, and AMU on census data of approximately 17,000 dairy herds, with about 1.67 million cows in total (>2 yr old) at one moment in time in the period from 2013 until 2017. Six udder health parameters were evaluated using multivariable population-averaged generalized estimating equation models. The year in which the ban on BDCT was introduced (2013) was compared with the period thereafter (2014-2017). Additionally, AMU_IMM and AMU_DCT were included as independent variables to evaluate whether the extent to which SDCT was implemented on the herd level was associated with udder health. Demographic parameters were included as potential confounders. Since the ban on BDCT, overall declines of 63% in AMU_DCT and 15% in AMU_IMM were observed. The raw data show an improvement in 5 out of 6 evaluated udder health parameters between 2013 and 2017. Nevertheless, the multivariable model results showed that the period since the ban on BDCT was associated with a small but significant increase in the percentage of cows with high somatic cell count (HSCC) and new HSCC (+0.41% and +0.06%, respectively). Additionally, the probability of belonging to the group of herds with more than 25% of primiparous cows having HSCC during the start of lactation increased slightly, associated with the period after which BDCT was banned (odds ratio = 1.08). The probability of belonging to the group of herds with more than 25% cows having a persistent HSCC during the dry period was not affected and bulk milk somatic cell count showed a slight but significant reduction. The only udder health parameter that notably worsened during the study period was the probability of belonging to the group of herds with more than 25% of multiparous cows with a new HSCC after the dry period, during the start of lactation (odds ratio = 1.23). In herds where the farmer decided not to apply any dry cow therapy (≈20% of all herds), all udder health parameters were poorer compared with herds in which dry cow therapy was applied to some extent. The ban on BDCT and implementation of SDCT in the Netherlands was associated with a considerable reduction in AMU without a major impairment in udder health at the national level. Although negative effects of changed dry cow management were observed in some herds, we conclude that SDCT can be introduced without substantial negative effects on udder health.

Epidemiological study to investigate the incidence and prevalence of clinical mastitis, peracute mastitis, metabolic disorders and peripartum disorders, on a dairy farm in a temperate zone in Japan

Background

Our aim was to investigate the incidence and prevalence of clinical mastitis, peracute mastitis, metabolic disorders, and peripartum disorders, and to examine factors affecting the prevalence of each disease in cows raised on a large dairy farm in a temperate climate in Japan. The present study was performed on a large commercial dairy farm with approximately 2500 Holstein cows. Data were collected from 2014 to 2018, and involved 9663 calving records for 4256 cows.

Results

The incidence rate on the farm was 21.9% for clinical mastitis, 10.4% for peracute mastitis, 2.9% for metabolic disorders, and 3.2% for peripartum disorders. The prevalence rates for clinical mastitis, peracute mastitis, metabolic disorders, and peripartum disorders were 28.0, 13.3, 3.7, and 4.0%, respectively. In all four diseases, the probability of time to occurrence for each disease was associated with parity and calving season (P < 0.05). Regarding metabolic disorders and peripartum disorders, the probability of occurrence decreased during the first 10 days after calving.

Conclusions

Our results showed that clinical mastitis occurred most often in this temperate zone, and that metabolic disorders and peripartum disorders occurred from calving to day 10 post-calving.

Financial and economic analyses of the impact of cattle mastitis on the profitability of Egyptian dairy farms

Aim:

This study aimed to evaluate and quantify the different factors affecting the costs of mastitis in cattle, to quantify the annual and monthly financial losses attributed to mastitis, and to estimate production losses using average linear scores found on The Dairy Herd Improvement Association somatic cell count (SCC) sheets and bulk tank SCC per lactation number.

Materials and Methods:

All data (bovine mastitis-associated costs and expenditures in Egyptian dairy herds) were analyzed using SPSS/PCT, 2001. A partial budget technique using spreadsheet software and the general linear model procedure was used to analyze the productive and financial measures.

Results:

Mastitis was present in 57.1% of cows (240/420), while clinical mastitis (CM) was present in 19% of them (80/420). The geometric mean of SCC/ml in bulk tank milk samples of 150 cattle dairy farms was 556.3×10³. The annual subclinical mastitis (SCM)-related economic loss was 21,933,258.6 LE, and the two most important cost components were the subsequent decrease in milk production and quality premium losses (93% and 7% of SCM costs, respectively). The quality premium loss was 1,369,602.1 LE. On the other hand, the annual economic loss due to decreased milk production as a result of SCM was 20,563,656.5 LE. The total cost of 80 CM cases, including the failure and preventive costs, was 1,196,871.4 LE, including 1,169,150.4 LE failure costs (106,336.0 LE in direct costs and 1,062,814.4 LE in indirect costs) and 27,721.0 LE preventive costs. The average cost per CM case was 28,760.9 LE, including veterinary time and consultation fees of 250.0 LE (1%), labor 562.5 LE (2%), premature culling 736,000.0 LE (77%), decreased milk production 4085.18 LE (13.7%), discarded milk 185.3 LE (1%), and drugs and treatments 328.9 LE (1%). The total costs of CM (expenditures) extra control and preventive measures, including the diagnosis of CM for 80 cows annually in 20 Egyptian dairy farms were 27,721.0 LE, representing 346.5 LE or 1% of the total cost of CM cases. The cost of monitoring and diagnostic measures was 8635.2 LE, representing 107.9 LE or 1% of the total cost of a case of CM.

Conclusion:

The method used for cost estimation, in this study, is highly adaptable to individual cattle farms and had a major role in assessing specific control and management measures. The concepts described in this paper help to improve our understanding of the full economic impact of clinical and subclinical mastitis in cattle in Egypt. Assessing the economic losses from mastitis to determine the economic costs and losses occurring in Egyptian dairy farms is critical for encouraging farmers to acknowledge the scale of the problem and implement effective management practices aimed at improving mastitis control and reducing the associated costs.

Assessment of udder health in lame cows

The objective of this study was to assess the udder health in lame dairy cows. The study was performed on 35 dairy cows which were admitted to the Clinic of Ruminants. The most frequent claw diseases were white line abscess (28.6%) and toe necrosis (28.6%), followed by digital dermatitis (17.1%), toe ulcers (14.3%), and sole ulcers (11.4%). The prevalence of mastitis in lame cows was 74.3% (26); clinical mastitis was detected in 5 (19.2%) and subclinical mastitis in 21 (80.8%) dairy cows. Distribution of mastitis was similar in terms of front (52.54%) and rear quarters (47.46%). For statistical analyses of mastitis grade in lame dairy cows, a six-point Mastitis Score was created based on physical examination of the mammary gland and results of California Mastitis Test. The Mastitis Score tended to be higher in cows with corium inflammation than in those with digital dermatitis (10.0 and 6.5, respectively). Microbiological culture of 24 positive milk samples was performed and intra-mammary pathogens were isolated in 18 (75%) samples. The most prevalent bacteria were coagulase negative staphylococci (50%), followed by Enterococcus spp. (16.7%), Proteus spp. (11.1%), and Aerococcus viridians (11.1%). Of the total bacteria, contagious pathogens were determined in two milk samples (11.1%). In conclusion, high prevalence of mastitis was detected in lame cows suffering from claw diseases without a significant effect of the type of claw diseases on the mastitis grade. Moreover, the dominating isolation of environmental pathogens may be a result of longer lying period of animals affected with lameness.

Comparing two approaches for meta-analysis of binary outcomes

In the present study, meta-analysis of binary outcome was undertaken by using two approaches namely Summary Statistics (SS) and Individual Animal Data (IAD) approach for obtaining more reliable estimates of the association of risk factors [breed (crossbred & indigenous), parity (primiparous & multiparous), age (< 5 years & > 5 years) and milk yield (kg)] with clinical mastitis [binary outcome (yes or No)] in dairy cows in India. For the present study the data on mastitis were compiled from three organized cattle farms. The results of bootstrapping showed that the pooled estimates under Individual Animal Data (IAD) approach were significantly higher than Summary Statistics (SS) appraoch for all unadjusted risk factors. However the results of both approaches were similar under covariate-adjusted circumstances. In case of heterogeneity of effects across farms, Individual Animal Data (IAD) approach provides more reliable information than Summary Statistics (SS) approach. Therfore it was also concluded that the crossbreds (adjusted for age) cows (1.47 times), older cows (1.85 times) multiparous cows (2.21 times) and high yielders (1.67 times) cows were at higher risk of mastitis than their respective reference categories. Therefore Individual Animal Data (IAD) approach is an appropriate approach for animal science data as it is more reliable and perform better in heterogenous conditions.

Symposium review: Real-time continuous decision making using big data on dairy farms

We are developing a real-time, data-integrated, data-driven, continuous decision-making engine, The Dairy Brain, by applying precision farming, big data analytics, and the Internet of Things. This is a transdisciplinary research and extension project that engages multidisciplinary scientists, dairy farmers, and industry professionals. Dairy farms have embraced large and diverse technological innovations such as sensors and robotic systems, and procured vast amounts of constant data streams, but they have not been able to integrate all this information effectively to improve whole-farm decision making. Consequently, the effects of all this new smart dairy farming are not being fully realized. It is imperative to develop a system that can collect, integrate, manage, and analyze on- and off-farm data in real time for practical and relevant actions. We are using the state-of-the-art database management system from the University of Wisconsin-Madison Center for High Throughput Computing to develop our Agricultural Data Hub that connects and analyzes cow and herd data on a permanent basis. This involves cleaning and normalizing the data as well as allowing data retrieval on demand. We illustrate our Dairy Brain concept with 3 practical applications: (1) nutritional grouping that provides a more accurate diet to lactating cows by automatically allocating cows to pens according to their nutritional requirements aggregating and analyzing data streams from management, feed, Dairy Herd Improvement (DHI), and milking parlor records; (2) early risk detection of clinical mastitis (CM) that identifies first-lactation cows under risk of developing CM by analyzing integrated data from genetic, management, and DHI records; and (3) predicting CM onset that recognizes cows at higher risk of contracting CM, by continuously integrating and analyzing data from management and the milking parlor. We demonstrate with these applications that it is possible to develop integrated continuous decision-support tools that could potentially reduce diet costs by $99/cow per yr and that it is possible to provide a new dimension for monitoring health events by identifying cows at higher risk of CM and by detecting 90% of CM cases a few milkings before disease onset. We are securely advancing toward our overarching goal of developing our Dairy Brain. This is an ongoing innovative project that is anticipated to transform how dairy farms operate.

Role of Liver X Receptor in Mastitis Therapy and Regulation of Milk Fat Synthesis

Mastitis is important disease that causes huge economic losses in the dairy industry. In recent years, antibiotic therapy has become the primary treatment for mastitis, however, due to drug residue in milk and food safety factors, we lack safe and effective drugs for treating mastitis. Therefore, new targets and drugs are urgently needed to control mastitis. LXRα, one of the main members of the nuclear receptor superfamily, is reported to play important roles in metabolism, infection and immunity. Activation of LXRα could inhibit LPS-induced mastitis. Furthermore, LXRα is reported to enhance milk fat production, thus, LXRα may serve as a new target for mastitis therapy and regulation of milk fat synthesis. This review summarizes the effects of LXRα in regulating milk fat synthesis and treatment of mastitis and highlights the potential agonists involved in both issues.

Transmission dynamics of Staphylococcus aureus within two Danish dairy cattle herds

Staphylococcus aureus is a major pathogen causing intramammary infections (IMI) in dairy cattle herds worldwide. Simulation models can be used to investigate the epidemiologic and economic outcomes of different control strategies against IMI. The transmission rate parameter is one of the most influential parameters on the outcomes of these simulation models. Very few studies have estimated the transmission rate parameter and investigated the transmission dynamics of Staph. aureus IMI in dairy cattle herds. The objective of our study was therefore to analyze the transmission dynamics of Staph. aureus in 2 Danish dairy herds participating in a longitudinal study. The 2 herds had 180 and 360 milking cows, and animals were tested at quarter level once per month over a period of 1 yr. We estimated the quarter-level prevalence to be 34% for herd 1 and 2.57% for herd 2. The daily quarter-level transmission rate was estimated to be 0.0132 and 0.0077 cases/quarter-day for herds 1 and 2, respectively, and the median duration of infection was estimated to be 91 and 64 d for herds 1 and 2, respectively. We also estimated the reproductive ratio at 1.21 for herd 1 and 0.52 for herd 2. The results can provide valuable information for simulation models to aid decision-making in terms of the prevention and control of Staph. aureus IMI in dairy cattle herds.

Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle

Background

Improving resistance to mastitis, one of the costliest diseases in dairy production, has become an important objective in dairy cattle breeding. However, mastitis resistance is influenced by many genes involved in multiple processes, including the response to infection, inflammation, and post-infection healing. Low genetic heritability, environmental variations, and farm management differences further complicate the identification of links between genetic variants and mastitis resistance. Consequently, studies of the genetics of variation in mastitis resistance in dairy cattle lack agreement about the responsible genes.

Results

We associated 15,552,968 imputed whole-genome sequencing markers for 5147 Nordic Holstein cattle with mastitis resistance in a genome-wide association study (GWAS). Next, we augmented P-values for markers in genes in the associated regions using Gene Ontology terms, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and mammalian phenotype database. To confirm results of gene-based analyses, we used gene expression data from E. coli-challenged cow udders. We identified 22 independent quantitative trait loci (QTL) that collectively explained 14% of the variance in breeding values for resistance to clinical mastitis (CM). Using association test statistics with multiple pieces of independent information on gene function and differential expression during bacterial infection, we suggested putative causal genes with biological relevance for 12 QTL affecting resistance to CM in dairy cattle.

Conclusion

Combining information on the nearest positional genes, gene-based analyses, and differential gene expression data from RNA-seq, we identified putative causal genes (candidate genes with biological evidence) in QTL for mastitis resistance in Nordic Holstein cattle. The same strategy can be applied for other traits.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5050-x) contains supplementary material, which is available to authorized users.

Dynamic forecasting of individual cow milk yield in automatic milking systems

Accurate forecasting of dairy cow milk yield is useful to dairy farmers, both in relation to financial planning and for detection of deviating yield patterns, which can be an indicator of mastitis and other diseases. In this study we developed a dynamic linear model (DLM) designed to forecast milk yields of individual cows per milking, as they are milked in milking robots. The DLM implements a Wood's function to account for the expected total daily milk yield. It further implements a second-degree polynomial function to account for the effect of the time intervals between milkings on the proportion of the expected total daily milk yield. By combining these 2 functions in a dynamic framework, the DLM was able to continuously forecast the amount of milk to be produced in a given milking. Data from 169,774 milkings on 5 different farms in 2 different countries were used in this study. A separate farm-specific implementation of the DLM was made for each of the 5 farms. To determine which factors would influence the forecast accuracy, the standardized forecast errors of the DLM were described with a linear mixed effects model (lme). This lme included lactation stage (early, middle, or late), somatic cell count (SCC) level (nonelevated or elevated), and whether or not the proper farm-specific version of the DLM was used. The standardized forecast errors of the DLM were only affected by SCC level and interactions between SCC level and lactation stage. Therefore, we concluded that the implementation of Wood's function combined with a second-degree polynomial is useful for dynamic modeling of milk yield in milking robots, and that this model has potential to be used as part of a mastitis detection system.

Invited review: Incidence, risk factors, and effects of clinical mastitis recurrence in dairy cows

Clinical mastitis (CM) is one of the most frequent and costly diseases in dairy cows. A frustrating aspect of CM is its recurrent nature. This review was conducted to synthesize knowledge on risk of repeated cases of CM, effects of recurrent CM cases, and risk factors for CM recurrence. A systematic review methodology was used to identify articles for this narrative review. Searches were performed to identify relevant scientific literature published after 1989 in English or French from 2 databases (PubMed and CAB Abstracts) and 1 search platform (Web of Science). Fifty-seven manuscripts were selected for qualitative synthesis according to the inclusion criteria. Among the 57 manuscripts selected in this review, a description of CM recurrence, its risk factors, and effects were investigated and reported in 33, 37, and 19 selected manuscripts, respectively. Meta-analysis and meta-regression analyses were used to compute risk ratio comparing risk of CM in cows that already had 1 CM event in the current lactation with risk of CM in healthy cows. For these analyses, 9 manuscripts that reported the total number of lactations followed and the number of lactations with ≤1 and ≤2 CM cases were used. When summarizing results from studies requiring ≥5 d between CM events to consider a CM event as a new case, we observed no significant change in CM susceptibility following a first CM case (risk ratio: 0.99; 95% confidence interval: 0.86-1.14). However, for studies using a more liberal CM recurrence definition (i.e., only 24 h between CM events to consider new CM cases), we observed a 1.54 times greater CM risk (95% confidence interval: 1.20-1.97) for cows that already had 1 CM event in the current lactation compared with healthy cows. The most important risk factors for CM recurrence were parity (i.e., higher risk in older cows), a higher milk production, pathogen species involved in the preceding case, and whether a bacteriological cure was observed following the preceding case. The most important effects of recurrent CM were the milk yield reduction following a recurrent CM case, which was reported to be similar to that of the first CM case, and the increased risk of culling and mortality, which were reported to surpass those of first CM cases.

Determinants of antimicrobial treatment for udder health in Danish dairy cattle herds

Societal pressure to limit the use of antibiotics in livestock production systems, including dairy cattle systems, is consistently increasing. To motivate farmers to reduce antibiotic usage, it is important to understand the factors that determine whether a cow will be treated with antibiotics or not. If farmers' usual practices regarding antibiotic treatments are taken into account, they may be motivated to adopt control measures that can facilitate prudent use of antibiotics and are at the same time cost-effective. In this study, we analyzed database recordings of milk yield and somatic cell count from the routine milk recording scheme, clinical registrations of mastitis and PCR results, and cow factors such as days in milk and parity in relation to antibiotic treatments for 518 dairy herds in Denmark. Farm-wise logistic regressions were used to predict antimicrobial treatment based on these factors. The resulting regression coefficients of 422 herds were further analyzed by principal component analysis and clustering to determine the driving predictors for treatment in different groups of farms. The results showed that determinants that were most important for predicting antibiotic treatments vary from one farm to another. Health indicators such as PCR or somatic cell count were most indicative for treatment on some farms, whereas other groups seemed to depend more on production factors (milk yield) or later culling of the cows. This shows that farmers behave differently and differences can be identified in register data. This information can be considered when developing cost-effective herd-specific control measures of mastitis to promote prudent use of antibiotics in Danish dairy cattle farms.

Relationship between intramammary infection prevalence and somatic cell score in commercial dairy herds

We examined consistency of the relationship between intramammary infection (IMI) and somatic cell score (SCS) across several classes of cow, herd, and sampling time variables. Microbial cultures of composite milk samples were performed by New York Quality Milk Production Services from 1992 to 2004. SCS was from the most recent Dairy Herd Improvement test before IMI sampling. Records were analyzed from 79,308 cows in 1,124 commercial dairy herds representing a broad range of production systems. Three binary dependent variables were presence or absence of contagious IMI, environmental IMI, and all IMI. Independent variables in the initial models were SCS, SCS², lactation number, days in milk, sample day milk yield, use of coliform mastitis vaccine, participant type (required by regulation or voluntary), production system (type of housing, milking system, and herd size), season of sampling, year of sampling, and herd; also the initial models included interactions of SCS and SCS² with other independent variables, except herd and milk yield. Interaction terms characterize differences in the IMI-SCS relationship across classes of the independent variables. Models were derived using the Glimmix macro in SAS (SAS Institute Inc., Cary, NC) with a logistic link function and employing backward elimination. The final model for each dependent variable included all significant independent variables and interactions. Simplified models omitted SCS² and all interactions with SCS. Interactions of SCS with days in milk, use of coliform mastitis vaccine, participant type, season, and year were not significant in any of the models. Interaction of SCS with production system was significant for the all IMI model, whereas interaction of SCS with lactation number was significant for the environmental and all IMI models. Each 1-point increase in SCS (or doubling of somatic cell count) was associated with a 2.3, 5.5, and 9.1% increase in prevalence of contagious, environmental, and all IMI, respectively. Empirical receiver operator characteristic curves and areas under the curve were derived for final and simplified models. The areas under the curve for simplified and final models within each type of IMI differed by 0.009 or less. We concluded that the relationship of IMI with SCS was generally stable over time and consistent across seasons, production systems, and cow factors.

Distribution of non-aureus staphylococci species in udder quarters with low and high somatic cell count, and clinical mastitis

The effect of non-aureus staphylococci (NAS) in bovine mammary health is controversial. Overall, NAS intramammary infections (IMI) increase somatic cell count (SCC), with an effect categorized as mild, mostly causing subclinical or mild to moderate clinical mastitis. However, based on recent studies, specific NAS may affect the udder more severely. Some of these apparent discrepancies could be attributed to the large number of species that compose the NAS group. The objectives of this study were to determine (1) the SCC of quarters infected by individual NAS species compared with NAS as a group, culture-negative, and major pathogen-infected quarters; (2) the distribution of NAS species isolated from quarters with low SCC (<200,000 cells/mL) and high SCC (≥200,000 cells/mL), and clinical mastitis; and (3) the prevalence of NAS species across quarters with low and high SCC. A total of 5,507 NAS isolates, 3,561 from low SCC quarters, 1,873 from high SCC quarters, and 73 from clinical mastitis cases, were obtained from the National Cohort of Dairy Farms of the Canadian Bovine Mastitis Research Network. Of quarters with low SCC, high SCC, or clinical mastitis, 7.6, 18.5, and 4.3% were NAS positive, respectively. The effect of NAS IMI on SCC was estimated using mixed-effect linear regression; prevalence of NAS IMI was estimated using Bayesian analyses. Mean SCC of NAS-positive quarters was 70,000 cells/mL, which was higher than culture-negative quarters (32,000 cells/mL) and lower than major pathogen-positive quarters (129,000 to 183,000 cells/mL). Compared with other NAS species, SCC was highest in quarters positive for Staphylococcus capitis, Staphylococcus gallinarum, Staphylococcus hyicus, Staphylococcus agnetis, or Staphylococcus simulans. In NAS-positive quarters, Staphylococcus xylosus (12.6%), Staphylococcus cohnii (3.1%), and Staphylococcus equorum (0.6%) were more frequently isolated from quarters with low SCC than other NAS species, whereas Staphylococcus sciuri (14%) was most frequently isolated from clinical mastitis cases. Finally, in NAS-positive quarters, Staphylococcus chromogenes, S. simulans, Staphylococcus epidermidis, and Staphylococcus haemolyticus were isolated with similar frequency from among low SCC and high SCC quarters and clinical mastitis cases. Staphylococcus chromogenes, S. simulans, S. xylosus, S. haemolyticus, S. epidermidis, S. agnetis, Staphylococcus arlettae, S. capitis, S. gallinarum, S. sciuri, and Staphylococcus warneri were more prevalent in high than in low SCC quarters. Because the NAS are a large, heterogeneous group, considering them as a single group rather than at the species, or even subspecies level, has undoubtedly contributed to apparent discrepancies among studies as to their distribution and importance in IMI and mastitis.

Bivariate threshold models for genetic evaluation of susceptibility to and ability to recover from mastitis in Danish Holstein cows

Mastitis in dairy cows is an unavoidable problem and genetic variation in recovery from mastitis, in addition to susceptibility, is therefore of interest. Genetic parameters for susceptibility to and recovery from mastitis were estimated for Danish Holstein-Friesian cows using data from automatic milking systems equipped with online somatic cell count measuring units. The somatic cell count measurements were converted to elevated mastitis risk, a continuous variable [on a (0-1) scale] indicating the risk of mastitis. Risk values >0.6 were assumed to indicate that a cow had mastitis. For each cow and lactation, the sequence of health states (mastitic or healthy) was converted to a weekly transition: 0 if the cow stayed within the same state and 1 if the cow changed state. The result was 2 series of transitions: one for healthy to diseased (HD, to model mastitis susceptibility) and the other for diseased to healthy (DH, to model recovery ability). The 2 series of transitions were analyzed with bivariate threshold models, including several systematic effects and a function of time. The model included effects of herd, parity, herd-test-week, permanent environment (to account for the repetitive nature of transition records from a cow) plus two time-varying effects (lactation stage and time within episode). In early lactation, there was an increased risk of getting mastitis but the risk remained stable afterwards. Mean recovery rate was 45% per lactation. Heritabilities were 0.07 [posterior mean of standard deviations (PSD) = 0.03] for HD and 0.08 (PSD = 0.03) for DH. The genetic correlation between HD and DH has a posterior mean of -0.83 (PSD = 0.13). Although susceptibility and recovery from mastitis are strongly negatively correlated, recovery can be considered as a new trait for selection.

Meta-analysis of the prevalence of mastitis and associated risk factors in dairy cattle in Ethiopia

Mastitis is among the most prevalent disease that contributes for the reduction of milk production in dairy herds. Although several published studies have estimated the prevalence of mastitis, variation among studies is great. The objective of the present meta-analysis was to provide a pooled estimate of the prevalence of overall, clinical, and subclinical mastitis in dairy cattle in Ethiopia. A pooled estimate was also conducted by potential risk factors. The literature search was restricted to studies published in English language from January 2002 to June 2016. Meta-analysis of 39 studies was done under random effects model using metafor package in R software. The pooled estimate of the overall prevalence of mastitis on cow-basis was found to be 47.0% (95% confidence interval [CI] = 42.0, 52.0). The pooled prevalence with the 95% CI for clinical and subclinical mastitis was 8.3% (95% CI = 6.5, 10.3) and 37% (95% CI = 32.9, 40.7) respectively. There is a statistically significant and high heterogeneity of the prevalence estimates between published studies. The odds of occurrence of mastitis were higher in cows at early (odds ratio [OR] = 1.6; 95% CI = 1.4, 1.8) and late lactation (OR = 1.3; 95% CI = 1.2, 1.5) than mid lactation, in cows with 3-4 (OR = 1.5; 95% CI = 1.4, 1.7) and >4 parity number (OR = 2.9; 95% CI = 2.6, 3.4) than those with 1-2 parity number. Previous history of mastitis, floor type, milking hygiene, and udder injury had also statistically significant effect on pooled prevalence of mastitis (P < 0.05). The present study reported that there is high prevalence of mastitis in dairy cows in Ethiopia, which could contribute to the low productivity in lactating cows. The statistically significant association of risk factors such as floor type, milking hygiene, and presence of udder injury with mastitis may suggest that dairy farmers can reduce the occurrence of the disease by improving their management practices.

Stochastic bio-economic modeling of mastitis in Ethiopian dairy farms

Mastitis is an inflammation of the mammary gland that is considered to be one of the most frequent and costly diseases in the dairy industry. Also in Ethiopia, bovine mastitis is one of the most frequently encountered diseases of dairy cows. However, there was no study, so far, regarding the costs of clinical mastitis and only two studies were reported on costs of subclinical mastitis. Presenting an appropriate and complete study of the costs of mastitis will help farmers in making management decisions for mastitis control. The objective of this study was to estimate the economic effects of mastitis on Ethiopian market-oriented dairy farms. Market-oriented dairy farming is driven by making profits through selling milk in the market on a regular basis. A dynamic stochastic Monte-Carlo simulation model (bio-economic model) was developed taking into account both clinical and subclinical mastitis. Production losses, culling, veterinarian costs, treatment, discarded milk, and labour were the main cost factors which were modeled in this study. The annual incidence of clinical mastitis varied from 0 to 50% with a mean annual incidence of 21.6%, whereas the mean annual incidence of subclinical mastitis was 36.2% which varied between 0 and 75%. The total costs due to mastitis for a default farm size of 8 lactating cows were 6,709 ETB per year (838 ETB per cow per year). The costs varied considerably, with 5th and 95th percentiles of 109 ETB and 22,009 ETB, respectively. The factor most contributing to the total annual cost of mastitis was culling. On average a clinical case costs 3,631 ETB, varying from 0 to 12,401, whereas a sub clinical case costs 147 ETB, varying from 0 to 412. The sensitivity analysis showed that the total costs at the farm level were most sensitive for variation in the probability of occurrence of clinical mastitis and the probability of culling. This study helps farmers to raise awareness about the actual costs of mastitis and motivate them to timely treat and/or take preventive measures. As a results, the dairy industry will improve.

Mastitis Pathogens with High Virulence in a Mouse Model Produce a Distinct Cytokine Profile In Vivo

Mastitis is a serious medical condition of dairy cattle. Here, we evaluated whether the degree of virulence of mastitis pathogens in a mouse model can be linked to the inflammatory response that they provoke. Clinical isolates of Staphylococcus aureus (S. aureus) (strain 556 and 392) and Escherichia coli (E. coli) (676 and 127), and laboratory control strains [8325-4 (S. aureus) and MG1655 (E. coli)], were injected i.p. into mice, followed by the assessment of clinical scores and inflammatory parameters. As judged by clinical scoring, E. coli 127 exhibited the largest degree of virulence among the strains. All bacterial strains induced neutrophil recruitment. However, whereas E. coli 127 induced high peritoneal levels of CXCL1, G-CSF, and CCL2, strikingly lower levels of these were induced by the less virulent bacterial strains. High concentrations of these compounds were also seen in blood samples taken from animals infected with E. coli 127, suggesting systemic inflammation. Moreover, the levels of CXCL1 and G-CSF, both in the peritoneal fluid and in plasma, correlated with clinical score. Together, these findings suggest that highly virulent clinical mastitis isolates produce a distinct cytokine profile that shows a close correlation with the severity of the bacterial infection.

Reisolation of Staphylococcus aureus from bovine milk following experimental inoculation is influenced by fat percentage and specific immunoglobulin G1 titer in milk

The associations of management parameters, herd characteristics, and individual cow factors with bovine mastitis have been subject of many studies. The present study aimed to evaluate the association between milk composition parameters, including fat, protein, lactose, urea, and specific immunoglobulin levels, at the time of experimental bacterial inoculation of the mammary gland and subsequent shedding dynamics of Staphylococcus aureus. Sixty-eight cows were experimentally infected with S. aureus and closely monitored for 3 wk. Mixed model analyses were used to determine the influence of management and herd characteristics (farm and experimental group), individual cow factors (days in milk, milk yield, and quarter position), and a challenge-related parameter (inoculation dose) in combination with either the milk components fat, protein, lactose and urea, or the S. aureus-specific antibody isotype titers at the time of bacterial inoculation, on the number of S. aureus reisolated from milk after inoculation. A positive association was observed between the milk fat percentage and the number of S. aureus reisolated from quarter milk, and a negative relationship between the S. aureus-specific IgG1 titer in milk and the number of S. aureus. These findings should be considered in the development of a vaccine against S. aureus-induced bovine mastitis.

Evidence of no protection for a recurrent case of pathogen specific clinical mastitis from a previous case

The objective of this study was to determine whether the occurrence of a previous case of pathogen-specific clinical mastitis (CM) protects Holstein dairy cows against a recurrent case. Pathogens studied were Escherichia coli, Staphylococcus aureus, Staphylococcus spp., Streptococcus spp., Klebsiella spp., and Trueperella pyogenes. A total of 40 864 lactations (17,265 primiparous and 23,599 multiparous) from 19 835 cows from 5 large, high milk producing New York State dairy herds were analysed. We estimated the effects of parity, calving diseases, milk yield, current season and number of CM cases in the previous lactation on the risk of a first CM case using generalised linear mixed models with a log link and Poisson error distribution. The aforementioned risk factors and the occurrence of previous cases of pathogen-specific CM within the current lactation were evaluated as risks for second and third cases of pathogen-specific CM. Cows with more CM cases in the previous lactation were at greater risk of pathogen-specific CM in the current lactation. Multiparous cows were at greater risk of a second CM case if they had suffered from a first CM case that was caused by the same pathogen as the second case. In contrast, a second CM case generally put cows at greater risk of a third case, irrespective of whether the third case was caused by the same or a different pathogen. Our results showed that a previous case of pathogen specific CM does not generally protect against a recurrent case.

Investigation of the association between the test day milk fat-protein ratio and clinical mastitis using a Poisson regression approach for analysis of time-to-event data

The objective of the present study was to investigate the association between the milk fat-protein ratio and the incidence rate of clinical mastitis including repeated cases of clinical mastitis to determine the usefulness of this association to monitor metabolic disorders as risk factors for udder health. Herd records from 10 dairy herds of Holstein cows in Saxony, Germany, from September 2005-2011 (36,827 lactations of 17,657 cows) were used for statistical analysis. A mixed Poisson regression model with the weekly incidence rate of clinical mastitis as outcome variable was fitted. The model included repeated events of the outcome, time-varying covariates and multilevel clustering. Because the recording of clinical mastitis might have been imperfect, a probabilistic bias analysis was conducted to assess the impact of the misclassification of clinical mastitis on the conventional results. The lactational incidence of clinical mastitis was 38.2%. In 36.2% and 34.9% of the lactations, there was at least one dairy herd test day with a fat-protein ratio of <1.0 or >1.5, respectively. Misclassification of clinical mastitis was assumed to have resulted in bias towards the null. A clinical mastitis case increased the incidence rate of following cases of the same cow. Fat-protein ratios of <1.0 and >1.5 were associated with higher incidence rates of clinical mastitis depending on week in milk. The effect of a fat-protein ratio >1.5 on the incidence rate of clinical mastitis increased considerably over the course of lactation, whereas the effect of a fat-protein ratio <1.0 decreased. Fat-protein ratios <1.0 or >1.5 on the precedent test days of all cows irrespective of their time in milk seemed to be better predictors for clinical mastitis than the first test day results per lactation.

Invited review: Inflammation during the transition to lactation: New adventures with an old flame

For dairy cattle, the first several weeks of lactation represent the highest-risk period in their lives after their own neonatal period. Although more than 50% of cows during this period are estimated to suffer from at least one subclinical disorder, the complicated admixture of normal adaptations to lactation, infectious challenges, and metabolic disorders has made it difficult to determine which physiological processes are adaptive and which are pathological during this time. Subacute inflammation, a condition that has been well documented in obesity, has been a subject of great interest among dairy cattle physiologists in the past decade. Many studies have now clearly shown that essentially all cows experience some degree of systemic inflammation in the several days after parturition. The magnitude and likely persistence of the inflammatory state varies widely among cows, and several studies have linked the degree of postpartum inflammation to increased disease risk and decreased whole-lactation milk production. In addition to these associations, enhancing postpartum inflammation with repeated subacute administration of cytokines has impaired productivity and markers of health, whereas targeted use of nonsteroidal anti-inflammatory drugs during this window of time has enhanced whole-lactation productivity in several studies. Despite these findings, many questions remain about postpartum inflammation, including which organs are key initiators of this state and what signaling molecules are responsible for systemic and tissue-specific inflammatory states. Continued in vivo work should help clarify the degree to which mild postpartum inflammation is adaptive and whether the targeted use of anti-inflammatory drugs or nutrients can improve the health and productivity of dairy cows.