The detection of intramammary infections using online somatic cell counts

Abstract

Timely and accurate identification of cows with intramammary infections is essential for optimal udder health management. Various sensor systems have been developed to provide udder health information that can be used as a decision support tool for the farmer. Among these sensors, the DeLaval Online Cell Counter (DeLaval, Tumba, Sweden) provides somatic cell counts from every milking at cow level. Our aim was to describe and evaluate diagnostic sensor properties of these online cell counts (OCC) for detecting an intramammary infection, defined as an episode of subclinical mastitis or a new case of clinical mastitis. The predictive abilities of a single OCC value, rolling averages of OCC values, and an elevated mastitis risk (EMR) variable were compared for their accuracy in identifying cows with episodes of subclinical mastitis or new cases of clinical mastitis. Detection of subclinical mastitis episodes by OCC was performed in 2 separate groups of different mastitis pathogens, Pat 1 and Pat 2, categorized by their known ability to increase somatic cell count. The data for this study were obtained in a field trial conducted in the dairy herd of the Norwegian University of Life Sciences. Altogether, 173 cows were sampled at least once during a 17-mo study period. The total number of quarter milk cultures was 5,330. The most common Pat 1 pathogens were Staphylococcus epidermidis, Staphylococcus aureus, and Streptococcus dysgalactiae. The most common Pat 2 pathogens were Corynebacterium bovis, Staphylococcus chromogenes, and Staphylococcus haemolyticus. The OCC were successfully recorded from 82,182 of 96,542 milkings during the study period. For episodes of subclinical mastitis the rolling 7-d average OCC and the EMR approach performed better than a single OCC value for detection of Pat 1 subclinical mastitis episodes. The EMR approach outperformed the OCC approaches for detection of Pat 2 subclinical mastitis episodes. For the 2 pathogen groups, the sensitivity of detection of subclinical mastitis episodes was 69% (Pat 1) and 31% (Pat 2), respectively, at a predefined specificity of 80% (EMR). All 3 approaches were equally good at detecting new cases of clinical mastitis, with an optimum sensitivity of 80% and specificity of 90% (single OCC value).

Dynamics of somatic cell count patterns as a proxy for transmission of mastitis pathogens

“…Plates were read at 24 and 48 h. We used a MALDI-TOF MS Microflex LT system (Bruker Corp., Billerica, MA;Cheuzeville, 2015) for species identification of cultured bacteria. Further details on the study herd, sampling framework, and microbial analyses were previously published (Dalen et al, 2019).…”

“…Also, because the same cow could experience a subclinical IMI episode with different mastitis pathogens at the same time, pathogens were divided into 2 groups (Pat 1 and Pat 2), according to characteristics of the bacteria. The group of pathogens from which a high cell count would be expected during a subclinical IMI episode was designated Pat 1, according to Dalen et al (2019). The pathogens included in the Pat 1 group were Staphylococcus aureus, Streptococcus dysgalactiae, Streptococcus uberis, Enterococcus faecalis, Enterococcus faecium, Lactococcus lactis, Staphylococcus epidermidis, and Staphylococcus simulans (Djabri et al, 2002;Reksen et al, 2008;Simojoki et al, 2009Simojoki et al, , 2011Fry et al, 2014).…”

“…This EMR indicator is a continuous variable (from 0 to 1), where values close to 0 indicate a low risk of mastitis and higher values, approaching 1, indicate an increased risk of clinical mastitis (Sørensen et al, 2016). Dalen et al (2019) demonstrated that the EMR indicator can be used to detect subclinical mastitis episodes in individual cows. However, when every milking is a potential detection event, the diagnostic test properties are insufficiently sensitive for direct application in a decision-support tool (Dalen et al, 2019).…”

“…Dalen et al (2019) demonstrated that the EMR indicator can be used to detect subclinical mastitis episodes in individual cows. However, when every milking is a potential detection event, the diagnostic test properties are insufficiently sensitive for direct application in a decision-support tool (Dalen et al, 2019). Therefore, the interpretation and use of OCC during lactation should be improved in decision-support tools for dairy farmers.…”

Milk quality in small farms from Southern Region of Brazil

“…The average values for somatic cell counts (SCC) and total plate counts (TPC) were higher than the limits in the Brazilian regulations (Figure 2 and 3), demonstrating that hygienic-sanitary management is deficient. The SCC is affected by incidence of mastitis and TPC is closely linked with the hygienic aspects of milking (DALEN et al, 2019;KIRKEBY et al, 2019).…”