Somatic Cell Count Distributions During Lactation Predict Clinical Mastitis

Abstract

This research investigated somatic cell count (SCC) records during lactation, with the purpose of identifying distribution characteristics (mean and measures of variation) that were most closely associated with clinical mastitis. Three separate data sets were used, one containing quarter SCC (n = 1444) and two containing cow SCC (n = 933 and 11,825). Clinical mastitis was defined as a binary outcome, present or absent, for each lactation, and SCC were log (base 10) transformed. A generalized linear mixed model within a Bayesian framework was used for analysis. Parameters were estimated using Markov Chain Monte Carlo with Gibbs sampling. Results from the 3 data sets were similar. Increased maximum and standard deviation log SCC during lactation, rather than increased geometric mean, were the best overall indicators of clinical mastitis. Distributions of SCC were also investigated separately for different mastitis pathogens. Increased maximum log SCC was associated with clinical mastitis caused by all pathogen types. Increased standard deviation log SCC was associated with Staphylococcus aureus, and Streptococcus uberis clinical mastitis and increased coefficient of variation log SCC (standard deviation divided by mean) was associated with Escherichia coli clinical mastitis. Increased geometric mean lactation SCC was associated with an increased risk of Staph. aureus clinical mastitis but a reduced risk of E. coli clinical mastitis. Our results suggest that using measures of variation and maximum cow SCC would enhance the accuracy of predicting clinical mastitis, compared with geometric mean SCC, and therefore improve genetic programs that aim to select for clinical mastitis resistance. The results are also consistent with low SCC increasing susceptibility to some mastitis pathogens.

Somaticell® as a screening method for somatic cell count from bovine milk

“…Somatic cell counts are a useful measure of udder health (GREEN et al, 2004). Studies indicate that different pathogens are associated with different magnitude of SCC increase (DE HAAS et al, 2002;SCHREINER & RUEGG, 2003).…”

Genetic analysis of tolerance to infections using random regressions: a simulation study

“…1). The normal distribution covers burden traits that are normally distributed at least after a transformation, such as log-normally and normally distributed pathogen/parasite counts, production diseases such as mastitis in dairy cows or ascites measured as a heart ratio in broilers (Green et al, 2004 ;Zerehdaran et al, 2006 ;Kuukka-Anttila et al, 2010). The negative binomial distribution, in turn, is perhaps the most widely used distribution to describe empirical parasite/parasitoid burdens (Stear et al, 1995).…”

Partial budget analysis of prepartum antimicrobial therapy and Escherichia coli J5 vaccination of dairy heifers and their effect on milk production and milk quality parameters

“…In regard to the higher incidence rate of clinical mastitis in first-calving compared with multiparous cows , Compton et al 2009, Piepers et al 2009, De Vliegher et al 2012) and the results of the present study, the use of antimicrobial therapy and/or E. coli J5 vaccination can be justified by the lower incidence of clinical mastitis and consequently the lower volume of discarded milk and the related economic benefits, especially in well-managed dairy herds (Green et al 2004).…”

“…In the last few decades with the improvement of subclinical mastitis control programs, which has led to herds with a lower somatic cell count (SCC), clinical mastitis has become a major problem in many well-managed dairy herds that have successfully controlled contagious pathogens (Green et al 2004).…”