The objective of this study was to further scrutinize the previously found positive association between intramammary infection (IMI) caused by coagulase-negative staphylococci (CNS) in early lactating heifers and test-day daily milk yield (MY) throughout first lactation, with a specific focus on the effect of the heifers' genetically determined milk production levels and the incidence of clinical mastitis. Two precise longitudinal data sets were analyzed using a series of statistical models including potential confounding and intermediate variables. The final database included the IMI status at calving, composite milk somatic cell count (SCC) and MY records at test day up to 285 d in milk (DIM), farmer-recorded clinical mastitis (CM) cases between 14 and 285 DIM, estimated new IMI incidence based on a SCC threshold of 100,000 cells/mL between 14 and 285 DIM, DIM, average 305-d MY at the herd level, and the heifers' genetic merit for MY from 240 dairy heifers from 29 dairy herds. Seventy-one (29.6%) early lactating heifers were noninfected, 108 heifers (45.0%) were CNS infected, and 61 heifers (25.4%) were infected with any major pathogen. The positive effect of CNS IMI in early lactation on test-day MY was estimated at 1.32 kg/d using a first basic mixed regression model. Correcting for the confounder genetic merit for MY reduced this effect to 1.17 kg. Interestingly, taking into account the confounding effect of herd resulted in an increase of the estimate from 1.32 to 2.2 kg/d. The positive effect of CNS IMI in early lactation on MY after correcting the model for both confounders was estimated at 2.05 kg/d. Heifers infected with CNS in the first DIM tended to have fewer CM cases throughout lactation compared with the noninfected herd mates. Including the intermediate variable CM in the model explained 0.16 kg/d of the corrected effect of 2.05 kg/d. Inclusion of test-day SCC, another intermediate variable, however, increased the estimate by 0.11 kg/d. With an appropriate correction for several confounders and biologically understood intermediate variables such as CM, test-day SCC, and new IMI based on SCC threshold of 100,000 cells/mL, an unexplained test-day MY difference between CNS-infected and noninfected heifers of 2.0 kg/d remained.

Associations between herd management practices and both bacterial counts (BC) and coliform counts (CC) from 254 and 242 dairy herds in Flanders (Belgium), respectively, were studied. Data were analyzed using multivariable, multilevel linear regression analysis, allowing variance components analyses. Both BC and CC fluctuated throughout the year, although the milk quality parameters followed an opposite pattern. Bacterial count values decreased with each increase of the cleaning frequency of the cubicles (once per week, once per day, twice per day, or more than twice per day) between January and March. Herds with a conventional milking parlor had substantially lower BC than herds where the cows were milked using an automatic milking system. Lower BC were observed when the milking parlor was equipped with an automatic cluster removal system, when premilking teat disinfection was applied, when the dry cows were supplemented with a mix of minerals and vitamins, and when the teats were prepared either first wet and dried or via an automatic milking system. Milking cows with a high-pipeline milking parlor setup or with an automatic milking system was associated with substantially higher CC values. Herds where prepartum heifers were often treated with antimicrobials before calving had a lower CC than farms where heifers were either not or only rarely treated. Most variation in BC and CC resided at the herd level rather than at the observation level, indicating that management is important in the control of both BC and CC. Still, only a small proportion of the total variance was explained by factors capturing information related to the milking, herd health, and dry cow management, which suggests that the bacteriological milk quality and, in particular, CC is primarily driven by other factors than the ones included in this study.

No abstract

Prepartum intramammary treatment with antimicrobials of end-term dairy heifers has frequently been proposed as a practice to reduce the prevalence of intramammary infections (IMI) at calving. From a safety standpoint for both animal and administrator, systemic treatment is preferred. A clinical trial was conducted on heifers from 10 well-managed, commercial dairy farms with a low prevalence of heifer mastitis. The aim was to assess both the short- and long-term effects of a systemic prepartum therapy with penethamate hydriodide on udder health and milk production. Because it was hypothesized that some herds would benefit more from this treatment than others, specific herd-level information was collected before the start of the actual trial to screen for and explain potential herd-specific treatment effects. Further, the effect of treatment on antimicrobial susceptibility of staphylococcal isolates was monitored. End-term heifers were either treated systemically (over 3 consecutive days) 2 wk before expected calving date with penethamate hydriodide (n=76) or remained untreated (n=73). Systemic prepartum treatment of end-term heifers with penethamate hydriodide resulted in fewer IMI in early lactation. However, all 6 cases of clinical mastitis in early lactation occurred in the treatment group [Streptococcus uberis (n=1), Corynebacterium bovis (n=1), Staphylococcus aureus (n=1); 1 sample was contaminated; 2 samples remained culture negative]. No long-term treatment effects (from 4 to 120 d in milk) on milk production, udder health, or culling hazard during later lactation were detected, although treated heifers belonging to herds classified as having low-yielding heifers out-produced the control heifers. Moreover, penicillin susceptibility of staphylococci isolated from milk samples of treated or control heifers did not differ. Herds with a low prevalence of heifer mastitis are not likely to benefit from prepartum systemic antimicrobial treatment of the end-term heifers.

Heifer mastitis is a well-known problem, with several pathogens being involved. Several generic risk factors associated with the likelihood of intramammary infections (IMI) in fresh dairy heifers have been identified before. Yet, a need exists to identify pathogen group-specific factors, as the effect of (groups of) pathogens on udder health and milk yield is different. The aim of the present study was to identify pathogen group-specific risk factors for IMI in heifers participating in a prepartum antimicrobial treatment trial, allowing us to test the hypothesis that different factors are of importance between treated and untreated control heifers as well. Data from a clinical trial in which end-term heifers were treated systemically (over 3 consecutive days) 2 wk before calving with penethamate hydriodide (n=76) or remained untreated (n=73), were available. Several potential risk factors at the herd, heifer, and quarter level were recorded in the first 3 d in milk. Quarters from untreated heifers supplemented with ≥4 mg of selenium/d prepartum were significantly less likely to be infected with coagulase-negative staphylococci (CNS), whereas quarters were more likely to be infected with CNS when assistance during calving was needed. Udder edema before calving significantly decreased the odds of IMI with major pathogens. In treated heifers, no factors were detected that were associated with the likelihood of CNS IMI, whereas quarters from heifers were significantly more likely to be infected with major pathogens when they were housed in the calving pen more than 1 d and when they had been in contact with the lactating cows before calving. The risk factors for IMI that were identified in treated heifers were different than those in untreated heifers, independent of the pathogen group that was considered. It looks as if prepartum treatment not only changed the likelihood of infection, but also the factors that were associated with infection. However, except for treated heifers with an IMI with major pathogens, only a small proportion of the variation could be explained in the final models. Therefore, factors other than those that were studied could explain the likelihood of infection.