Bayesian estimation of diagnostic accuracy of somatic cell counts history and on-farm milk culture using Petrifilm® to identify quarters or cows that should be treated with antimicrobials in selective treatment protocols at dry off

Abstract

Bayesian latent class models were used to estimate the test accuracy of cow-level somatic cell counts data, quarter-level Petrifilm® on-farm milk culture, and quarter-level standard milk bacteriology for the identification of quarters that should possibly be treated with antimicrobials at dry off in dairy cows. Considering the availability of SCC data, the easiness of using just the last DHI test, and the high neagtive predictive value that could be achieved, producers may consider using just the last DHI test as a potential tool to identify cows that should be treated with antimicrobials at dry off. It may be used alone or in combination with quarter-level on-farm Petrifilm® milk culture on high SCC cows to further reduce the use of antimicrobials by identifying quarters that need to be treated.