The incidence and aetiology of clinical bovine mastitis on 14 farms in Northland,New Zealand

AIM: To estimate the incidence of clinical mastitis and the frequency of isolation of mastitis-causing organisms from clinical cases in one lactation season (July 2005 to May 2006) on 14 dairy farms from the Northland region of New Zealand.

METHODS: Cases of clinical mastitis were determined by trained farm personnel who recorded the identity of affected cows. Pooled milk samples from affected quarter(s) were aseptically collected by the farm personnel, for microbiology. Mean numbers of affected cows and quarters were compared at the population and farm level per 305 cow-days-at-risk (DAR).

RESULTS: One or more cases of clinical mastitis occurred in 559/3,765 (14.8%) lactating cows. The average incidence of clinical mastitis was 0.19 cases per 305 DAR. The incidence in rear quarters (56.2%) was 1.3 times (p=0.027) that of front quarters (43.8%). The incidence of clinical mastitis and numbers of affected quarters were signifi cantly infl uenced by the stage of lactation (higher in early lactation), age (higher in older cows) and farm. At the cow level, the most common isolates were Staphylococcus aureus (23.7%) and Streptococcus uberis (23.3%). No causative organisms were identifi ed in 19.9% of the samples. Each cow had an average of 1.8 quarters affected during a case of clinical mastitis.

CONCLUSIONS: This study demonstrated a higher incidence of staphylococcal clinical mastitis on dairy farms from Northland than has been reported in other regions of New Zealand.     

Cost-effectiveness of diagnostic strategies using quantitative real-time PCR and bacterial culture to identify contagious mastitis cases in large dairy herds

Diagnostic strategies to detect contagious mastitis caused by Mycoplasma bovis, Staphylococcus aureus, and Streptococcus agalactiae in dairy herds during an outbreak have been minimally studied with regard to cost and diagnostic sensitivity. The objective of this cross-sectional study was to compare the cost-effectiveness of diagnostic strategies for identification of infected cows in two California dairy herds during contagious mastitis outbreaks.     

Investigation of the association between the interval from internal teat sealant administration to calving and early lactation clinical mastitis in New Zealand dairy heifers

AIMS: To examine the association between the interval from internal teat sealant (ITS) administration to calving and the incidence of farmer-recorded clinical mastitis in the first 30 days of lactation in pasture-based dairy heifers.

METHODS: Heifers that were administered an ITS by a single veterinary business in the South Island of New Zealand over the winter of 2014 were enrolled in a cross-sectional observational study. ITS was administered to all heifers on each participating farm on a single calendar day. The dates of calving and farmer-diagnosed clinical mastitis were recorded by farm staff. The interval from ITS administration to calving was categorised into four approximately evenly sized groups: <35, 35–48, 49–69 and >69 days. The quartile of the farm’s calving period in which each heifer calved was also investigated as a potential confounding variable. A hierarchical logistic regression model was constructed to determine the association between the interval from ITS administration to calving with the odds of clinical mastitis in the first 30 days of lactation.

RESULTS: Analysis was performed on 7,126 eligible heifers from 31 farms, with ITS administered between 9 May and 11 July 2014. The mean interval from ITS administration to calving was 52.9 (SD 24.4, min 1, max 137) days. Clinical mastitis was diagnosed in 420/7,126 (5.9 (95% CI=5.4–6.5)%) heifers between calving and day 30 of lactation. In the final multivariable model, which included calving period quartile, interval from ITS administration to calving was not associated with the odds of clinical mastitis (p=0.516). Compared to an interval from ITS administration to calving of <35 days, the adjusted OR of clinical mastitis for intervals of 35–48, 49–69 and >69 days were 0.83 (95% CI=0.59–1.17), 0.71 (95% CI=0.45–1.11) and 0.68 (95% CI=0.36–1.29), respectively.

CONCLUSIONS AND CLINICAL RELEVANCE: Within the range of intervals from ITS administration to calving observed in this study, there was no association with the odds of clinical mastitis in the first 30 days of lactation in dairy heifers. This study suggests that veterinary clinics may be able to extend their ITS administration service and treat dairy heifers earlier than the current recommendation of approximately 4 weeks before the planned start of calving.     

Effect of relationships among clinical mastitis incidence,reproductive performance,and culling rate on the lifetime of dairy cows at Hiroshima University Farm

Farm managers' decision to cull dairy cows is based on the cows' milk production, history of disorder(s), and reproductive performance, each of which affects dairy cows' lifetime (herd life and productive lifespan). We investigated the relationships among the incidence of clinical mastitis (CM), the reproductive performance, and the culling rate. We also assessed the effects of these relationships on the lifetimes of dairy cows, using the records made before and after the introduction of an automatic milking system (AMS) at Hiroshima University Farm. Milk yield, CM incidence density, and culling rate of dairy cows increased after the AMS introduction. The CM incidence was associated with an elongation of the calving interval in cows with the same parity. CM in the 1st parity might have caused the reductions of the cows' lifetime and their parity at culling. A higher age at first calving (AFC) was associated with an increase in culling rate but did not lead to a significant decrease in lifetime. Investigations of the factors mediating CM in the 1st parity or AFC with CM incidence or culling rate in the later stages might contribute to the control of lifetime of dairy cows.     

The use of Markov chain Monte Carlo for analysis of correlated binary data: patterns of somatic cells in milk and the risk of clinical mastitis in dairy cows

Two analytical approaches were used to investigate the relationship between somatic cell concentrations in monthly quarter milk samples and subsequent, naturally occurring clinical mastitis in three dairy herds. Firstly, cows with clinical mastitis were selected and a conventional matched analysis was used to compare affected and unaffected quarters of the same cow. The second analysis included all cows, and in order to overcome potential bias associated with the correlation structure, a hierarchical Bayesian generalised linear mixed model was specified. A Markov chain Monte Carlo (MCMC) approach, that is Gibbs sampling, was used to estimate parameters.

The results of both the matched analysis and the hierarchical modelling suggested that quarters with a somatic cell count (SCC) in the range 41,000–100,000 cells/ml had a lower risk of clinical mastitis during the next month than quarters <41,000 cell/ml. Quarters with an SCC >200,000 cells/ml were at the greatest risk of clinical mastitis in the next month. There was a reduced risk of clinical mastitis between 1 and 2 months later in quarters with an SCC of 81,000–150,000 cells/ml compared with quarters below this level. The hierarchical modelling analysis identified a further reduced risk of clinical mastitis between 2 and 3 months later in quarters with an SCC 61,000–150,000 cells/ml, compared to other quarters.

We conclude that low concentrations of somatic cells in milk are associated with increased risk of clinical mastitis, and that high concentrations are indicative of pre-existing immunological mobilisation against infection. The variation in risk between quarters of affected cows suggests that local quarter immunological events, rather than solely whole cow factors, have an important influence on the risk of clinical mastitis. MCMC proved a useful tool for estimating parameters in a hierarchical Bernoulli model. Model construction and an approach to assessing goodness of model fit are described.