Spatial and Temporal Patterns of Herd Somatic Cell Score in France

Spatial and temporal patterns of annual milk somatic cell score (ASCS) were explored in French dairy herds between 1996 and 2000 to detect regional singularities for risk of mastitis. A new cluster detection method was used, which was adapted to continuous variables and which allowed ASCS variation factors to be taken into account. The statistical unit was the herd-year. A linear regression model for each year allowed adjustment for breed, mean parity, number of calvings for each season, herd size, and farm altitude. Cluster detection was performed on raw data and on residuals of the model through a method based on the Hellinger distance between spatial distributions. The Hellinger distance between farm distributions was computed at different levels of ASCS (or residuals). Temporal ASCS patterns were explored using a computation of correlations and comparisons between spatial structures of the different years. The general ASCS trend over the study period was a decrease. The global Hellinger distance, which was higher than what could have been randomly expected for each of the 5 yr, indicated a significant spatial cluster formation. Cluster mapping over the 5 yr identified several areas, which sometimes differed between detection using raw data and that using ASCS residuals. Temporal correlations between ASCS residuals for each year were positive and decreasing, and 1996 and 2000 appeared spatially different from the other years. The more affected areas were regions that were not specialized in dairy production. During the study period, 2 progressive movements were detected, corresponding to a disappearance of clusters in the northwest and an increase of clusters in the southwest. Cluster detection could aid in the identification of new risk factors that are relevant at different spatial scales, and could help local organizations to supervise the risk of mastitis, and improve udder health management.