Abstract

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 ≥4mg 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.

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