Predicting the probability of abortion in dairy cows: a hierarchical Bayesian logistic-survival model using sequential pregnancy data.

Although abortion contributes substantially to poor reproductive health of dairy herds, little is known about the predictability of abortion based on age, previous abortion or gravidity (number of previous pregnancies). A poor understanding of effects of maternal factors on abortion risk exists, in part, because of methodological difficulties related to non-independence of multiple pregnancies of the same cow in analysis of fetal survival data. We prospectively examined sequential pregnancies to investigate relationships between fetal survival and putative dam risk factors for 2991 abortions from 24,706 pregnancies of 13,145 cows in nine California dairy herds. Relative risks and predicted probabilities of abortion (PPA) were estimated using a previously described hierarchical Bayesian logistic-survival model generalized to incorporate longitudinal data of multiple pregnancies from a single cow. The PPA increased with increasing dam age at conception, with increasing number of previous abortions, and if the previous pregnancy was aborted >60 days in gestation. The PPA decreased with increasing gravidity and with increasing number of days open. For cows that aborted, the median time to fetal death decreased slightly as gravidity increased. The study considers several methodological issues faced in epidemiologic investigations of fetal health, including multi-modal hazard functions, extensive censoring and non-independence of multiple pregnancies. The model improves our ability to predict bovine abortion and to characterize fetal survival, which have important applications to herd health management.