Transmission dynamics of Staphylococcus aureus and Streptococcus agalactiae in a Dutch dairy herd using an automatic milking system.

Staphylococcus aureus and Streptococcus agalactiae are important contagious mastitis pathogens and are considered to mainly transmit between cows through the milking machine. Controlling contagious mastitis on dairy farms requires a reduction of the transmission rate or the duration of intramammary infections (IMI), or both. These parameters may differ in dairy herds milked with an automatic milking system (AMS) as compared to those milked with a conventional milking system (CMS). The aims of this prospective longitudinal study were to estimate the transmission rate, the median duration of IMI and the basic reproduction number (R0) of Staph. aureus and Strep. agalactiae in a Dutch AMS herd. Bacteriological cultures of quarter milk samples were collected every 2 wks. Using 3 different definitions of IMI, we estimated the transmission rate for Staph. aureus to be within the range of 0.002 (95 % CI: 0-0.005) quarter-day-1 to 0.019 (95 % CI: 0.010-0.032) quarter-day-1, and for Strep. agalactiae of 0.007 (95 % CI: 0.005-0.010) quarter-day-1 to 0.019 (95 % CI: 0.011-0.032) quarter-day-1, the median duration of chronic IMI at 95 (95 % CI: 72-125) days for Staph. aureus and at 86 (95 % CI: 67-111) days for Strep. agalactiae, and the R0 between 0.16 (95 % CI: 0.05-0.27) and 0.34 (95 % CI: 0.20-0.48) for Staph. aureus, and between 0.64 (95 % CI: 0.41-0.87) and 0.68 (95 % CI: 0.48-0.88) for Strep. agalactiae. Transmission of these two contagious pathogens in this herd was limited and theoretically the IMI would not sustain, given that R0 of both pathogens was lower than 1. The estimated transmission rate of Staph. aureus in this AMS herd was found to be comparable to those described for CMS herds, while for Strep. agalactiae, it was slightly higher than in CMS herds. The duration of Staph. aureus IMI was in line with results from CMS farms, while the duration of Strep. agalactiae was lower than what has been described in CMS herds. The R0 of these contagious pathogens was found to be lower than the estimates in CMS herds. Our study suggests that the transmission rate of these two contagious pathogens in this AMS herd were comparable to what has been reported about well-performing CMS herds that have a low rate of transmission.

Performance of Online Somatic Cell Count Estimation in Automatic Milking Systems.

Somatic cell count (SCC) is one of the most important and widely used mastitis diagnostics. For detecting (sub)clinical mastitis, online SCC related measurements are more and more used in automatic milking systems (AMS). Sensors such as an automated online California Mastitis Test (O-CMT) allow for high frequency screening of high SCC cows within a herd, which makes it potentially powerful to identify episodes of mastitis. However, the performance of O-CMT measurements, as compared to SCC determined in the laboratory (L-SCC), has only scarcely been described. The aims of this study were (1) to assess the agreement between the O-CMT measurement averaged over different time windows and the corresponding L-SCC measurements; (2) to determine the optimal time window for averaging O-CMT as compared to L-SCC; (3) to explore the added value of time-series of frequent O-CMT measurements in individual cow udder health monitoring compared to L-SCC measurements. Data were collected from 50 farms in 6 different countries that were equipped with AMS using O-CMT measurements and also performed regular L-SCC testing. We found that the overall concordance correlation coefficient (CCC) between O-CMT and L-SCC was 0.53 but differed substantially between farms. The CCC between O-CMT and L-SCC improved when averaging O-CMT over multiple milkings, with an optimal time-window of 24 h. Exploration of time series of daily O-CMT recordings show that this is an effective screening tool to find episodes of high SCC. Altogether, we conclude that although O-CMT agrees moderately with L-SCC, because of its high measurement frequency, it is a promising on-farm tool for udder health monitoring.