Evaluation of test-day milk somatic cell count information to predict intramammary infection with major pathogens in dairy cattle at drying off

The objectives of this study were (1) to determine the test characteristics and predictive values of cow-level milk somatic cell count (SCC) information from (multiple) test-day recordings before drying off to identify major-pathogen-infected cows at drying off; and (2) to explore to what extent (an estimate of) the herd prevalence of subclinical mastitis, milk yield level, and parity of the cows affects the estimates. In total, 550 cows from 15 commercial dairy herds with overall good udder health management were dried-off during a study period of 6 mo. Test-day SCC were available through milk recording and within 5 d before drying off cows were sampled for quarter-level bacteriological culturing serving as the gold standard. Sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) were calculated at different threshold values of SCC, ranging between 50,000 and 500,000 cells/mL, to detect major-pathogen-infected cows. At a commonly used threshold of 200,000 cells/mL, the Se and Sp of (a combination of) test-day SCC before drying off ranged between 37.6 and 57.6% and between 66.7 and 79.3%, respectively. Still, estimates were modified by the herd level prevalence of subclinical mastitis and the cow's milk yield and parity. For instance, at the 200,000 cells/mL threshold using the geometric mean SCC of the 3 last test-days, the overall Se, Sp, PPV, and NPV were 37.6, 79.3, 30.8, and 83.9%, respectively, whereas these were 27.8, 87.5, 21.7, and 90.6%, respectively, for heifers and 40.3, 73.5, 33.3, and 78.9%, respectively, for multiparous cows. In conclusion, test-day SCC records obtained via milk recording are reliable to detect dairy cows at drying off that are not infected with major pathogens as determined by bacteriological culture and could eventually facilitate implementation of selective dry cow therapy in commercial dairy herds. Because estimates of the herd-level prevalence of subclinical mastitis, milk yield level, and parity of the cows affect the estimates of the test characteristics and predictive values to some extent, one should consider taking these parameters into account when differentiating infected from uninfected cows based on SCC data.