Estimates of dairy herd health indicators of mastitis, ketosis, inter-calving interval, and fresh cow replacement in the Piedmont region, Italy

Abstract

Test-day milk analysis has largely been used to study health and performance parameters in dairy cows. In this study, we estimated four health indicators of dairy cows using test-day data. Our purpose was to estimate (1) mastitis incidence rate, prevalence, and the probability of recovery; (2) the incidence proportion of ketosis; (3) the duration of inter-calving interval; and (4) the risk of a fresh cow being replaced, in a large cohort of dairy herds in the Piedmont region (Italy).We retrospectively analysed test day records of 261,121 lactating cows and 1315 herds during five years (2015–2020). Mastitis was defined by somatic cell count and ketosis by fat-to-protein ratio. Calving dates were used to calculate ICI and to estimate the removal of a fresh cow from the herd. Mixed-effect generalized linear models were used to adjust for unmeasured herd-level risk factors.The risk of mastitis increased by 120% with parity (Odds ratio [OR] = 2.20, confidence interval [CI]: 2.17 – 2.23), by 7% by months in milking (OR = 1.07, CI: 1.07 – 1.07), and even more if the cow was already affected during the same lactation (OR = 8.74, CI: 8.67 – 8.82). Lactose concentration on the previous test day was the best positive prognostic factor for mastitis recovery (OR = 1.12, CI: 1.08 – 1.17). Ketosis risk was the highest between 3rd and 4th lactations and itself increased the risk of having ICI longer than 440 days (OR = 1.12, CI: 1.02 – 1.22), and fresh-cow removal (OR = 1.75, CI: 1.58 – 1.93). Also, the removal of fresh cows was more likely when mastitis (OR = 1.31, CI: 1.19 – 1.45) or long ICI (OR = 1.34, CI: 1.22 – 1.48) occurred. For each health indicator, herd-level risk factors had an important role (18–56% of within-herd covariance).Our results indicate that milk analysis could be also useful for predicting mastitis, its cure rate, and ketosis. Cow-level risk factors are not enough to explain the risk of these issues. By studying a large population over a long period, this study provides an updated estimate of dairy cow health indicators in Piedmont (north-western Italy), useful for benchmarking dairy herds.