The main aim of the present study was to examine the economic consequences of a reduction in the incidence of clinical mastitis (CM) at herd level under current Swedish farming conditions. A second objective was to ask whether the estimated cost of CM alters depending upon whether the model reflects the fact that in different stages of lactation, CM gives rise to different yield-loss patterns or postulates just one type of yield-loss pattern irrespective of when, during lactation, CM occurs. A dynamic and stochastic simulation model, SimHerd, was used to study the effects of CM in a herd with 150 cows (9000 kg of energy-corrected milk per cow-year). Four herd types, defined by production level and reproductive performance, were modelled to investigate possible interactions between herd type and response to a reduction in the risk of CM. Technical and economic results, given the initial incidence of CM (25.6 per 100 cow-years), were studied together with the consequences of reducing the initial risk of CM by 50% and 90% throughout lactation and the consequences of reducing the initial risk by 50% and 90% before peak yield. A conventional way of modelling yield losses -i.e. one employing a single yield-loss pattern irrespective of when, during the lactation period, the cow develops CM -was compared with a new modelling strategy in which CM was assumed to affect production differently depending on its lactational timing. The effect of the choice of reference level when estimating yield losses was investigated by comparing the results obtained using the potential yield of mastitic cows, had they not developed CM, with those obtained using the yield of non-mastitic cows. The yearly maximum avoidable cost of CM at herd level was estimated at h14 504, corresponding to 6.9% of the net return given the initial incidence of CM. Expressed per cow-year, the maximum avoidable cost was h97. The cost per case of CM was estimated at h428. Herd types all responded in a similar manner to the reduced relative risk of CM. There were no major differences in the results obtained using the new and the conventional modelling strategy, with the exception of the cost per case of CM. Similarities between the results obtained using the two methods were particularly evident when the mastitic cows' own yield level, had they not developed CM, was used as the reference for production in healthy cows when yield losses were estimated. It was concluded that the conventional way of modelling yield losses is adequate and should, for the foreseeable future, be used in decision support systems.

The objective of this paper was to compare efficiency measures, milk production, and feed intake for lactating cows in commercial herds using different breeds and production and milking systems. To accomplish this, we used all feed evaluations made by the Danish extension service during the period November 2012 to April 2013 for 779 herds, of which 508 were Holstein-Friesian (HOL); 100 were Jersey (JER); and 171 herds were a mixture of these 2 breeds, other dairy breeds, and crossbreeds (OTH). The annually recorded, herd-average energy-corrected milk (ECM) yield was 8,716kg (JER) and 9,606kg (HOL); and average herd size was 197 cows (HOL) and 224 cows (JER). All cows were fed a total mixed or partial mixed ration supplemented with concentrate from feeding stations, housed in loose housing systems with a slatted floor, and milked in either a parlor milking unit or an automatic milking system. Energy efficiency was calculated as net energy efficiency defined as total energy demand as a percentage of energy intake and as residual feed intake defined as energy intake (net energy for lactation; NEL) minus energy requirement. Production efficiency was expressed as kilograms of ECM per kilogram of dry matter intake (DMI), kilograms of ECM per 10 MJ of net energy intake (NEL), kilograms of ECM per 100kg of BW, and kilograms of DMI per 100kg of BW. Environmental efficiency was expressed by the nitrogen efficiency calculated as N in milk and meat as a percentage of N in intake, and as enteric emission of methane expressed as kilograms of ECM per megajoule of CH4. Mean milk yield for lactating cows was 30.4kg of ECM in HOL and 3kg less in JER, with OTH herds in between. Mean NEL intake was 122 MJ in JER, increasing to 147 MJ in HOL, whereas ration energy density between breeds did not differ (6.4-6.5 MJ of NEL per kg of DMI). The NEL intake and DMI explained 56 and 47%, respectively, of variation in production (ECM) for HOL herds but only 44 and 27% for JER. Jersey had a higher efficiency than HOL and OTH, except in nitrogen efficiency, where no significant difference between breeds existed. Most of the efficiency measures were internally significantly correlated and in general highly positively correlated with milk production, whereas the correlation to DMI was less positive and for JER negative for net energy efficiency, kilograms of ECM per kilogram of DMI, and nitrogen efficiency. Only little of the variation in efficiency between herds could be explained by differences in nutrient or roughage content of DMI. This could be explained by the fact that data were collected from herds purchasing feed planning and evaluation from the extension service.

An automated method for determining whether dairy cows with subclinical mammary infections recover after antibiotic treatment would be a useful tool in dairy production. For that purpose, inline l-lactate dehydrogenase (LDH) measurements was modeled using a dynamic linear model; the variance parameters were estimated using the expectation-maximization algorithm. The method used to classify cows as infected or uninfected was based on a multiprocess Kalman filter. Two learning data sets were created: infected and uninfected. The infected data set consisted of records from 48 cows with subclinical Staphylococcus aureus infection from 4 herds collected in 2010. The uninfected data set came from 35 uninfected cows collected during 2013 from 2 herds. Bacteriological culturing was used as gold standard. To test the model, we collected data from the 48 infected cows 50 d after antibiotic treatment. As a result of the treatment, this test data set consisted of 25 cows that still had a subclinical infection and 23 cows that were recovered. Model sensitivity was 36.0% and specificity was 82.6%. To a large extent, l-lactate dehydrogenase reflected the cow's immune response to the presence of pathogens in the udder. However, cows that were classified correctly before treatment had a better chance of correct classification after treatment. This indicated a variation between cows in immune response to subclinical mammary infection that may complicate the detection of subclinically infected cows and determination of recovery.

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The aim of this observational retrospective cohort study was to identify management procedures that are associated with herd-level eradication of Streptococcus agalactiae in dairy herds. The objective was to compare herds that recovered from Strep. agalactiae with herds that remained infected with Strep. agalactiae on the basis of specific management procedures. Data from the Danish surveillance program for Strep. agalactiae, where all milk delivering dairy herds are tested yearly, were used to identify study herds. One hundred ninetysix herds that were classified in the program as infected