Screening tests for mastitis can play an important role in proactive mastitis control programs. The primary
objective of this study was to compare the sensitivity and specificity of milk electrical conductivity
(EC) to the California mastitis test (CMT) in commercial dairy cattle in South Africa using Bayesian methods
without a perfect reference test. A total of 1848 quarter milk specimens were collected from 173
cows sampled during six sequential farm visits. Of these samples, 25.8% yielded pathogenic bacterial isolates.
The most frequently isolated species were coagulase negative Staphylococci (n = 346), Streptococcus
agalactiae (n = 54), and Staphylococcus aureus (n = 42). The overall cow-level prevalence of mastitis was
54% based on the Bayesian latent class (BLC) analysis.
The CMT was more accurate than EC for classification of cows having somatic cell counts >200,000/mL
and for isolation of a bacterial pathogen. BLC analysis also suggested an overall benefit of CMT over EC but
the statistical evidence was not strong (P = 0.257). The Bayesian model estimated the sensitivity and
specificity of EC (measured via resistance) at a cut-point of >25 mO/cm to be 89.9% and 86.8%, respectively.
The CMT had a sensitivity and specificity of 94.5% and 77.7%, respectively, when evaluated at
the weak positive cut-point. EC was useful for identifying milk specimens harbouring pathogens but
was not able to differentiate among evaluated bacterial isolates. Screening tests can be used to improve
udder health as part of a proactive management plan.