Optimal replacement policies and economic value of clinical observations in sow herds

Abstract Even though several sow replacement models have been published, integrating information about the health status of sows has not yet been handled satisfactorily. This paper presents a framework for integrating a Weak Sow Index (WSI) into an existing sow replacement model. The WSI, which is developed as part of this study, quantifies various clinical signs into one numerical value representing the risk of a sow to be involuntarily culled. The objective of the study is to investigate the effect of observing clinical signs of sows on the optimal replacement policy. A second objective is to estimate the economic value of observing clinical signs of individual sows. Bayesian networks are used to develop the WSI models for lactating and pregnant sows, respectively. The optimization of the replacement policy is done in a multi-level hierarchical Markov decision process. To illustrate the behaviour of the model, the effect of the WSI on the replacement policy, and the economic benefit of observing clinical signs of individual sows are investigated in two fictitious herds with a high and a low risk of involuntary culling of sows. In general, the value of the WSI has a high influence on the optimal replacement policy, allowing for a better economic classification of sows when taking information about the health status into account. It is shown that the economic value of the WSI is higher in a high risk herd compared to a low risk herd. Among the individual clinical signs, “unwillingness to stand” made the lowest contribution to the economic value of the WSI. The highest contribution was made by the clinical sign “vulva bite” in pregnant sows.