E. Cha

The cost of different types of lameness in dairy cows calculated by dynamic programming.

Traditionally, studies which placed a monetary value on the effect of lameness have calculated the costs at the herd level and rarely have they been specific to different types of lameness. These costs which have been calculated from former studies are not particularly useful for farmers in making economically optimal decisions depending on individual cow characteristics. The objective of this study was to calculate the cost of different types of lameness at the individual cow level and thereby identify the optimal management decision for each of three representative lameness diagnoses. This model would provide a more informed decision making process in lameness management for maximal economic profitability. We made modifications to an existing dynamic optimization and simulation model, studying the effects of various factors (incidence of lameness, milk loss, pregnancy rate and treatment cost) on the cost of different types of lameness. The average cost per case (US

The cost and management of different types of clinical mastitis in dairy cows estimated by dynamic programming

) of sole ulcer, digital dermatitis and foot rot were 216.07, 132.96 and 120.70, respectively. It was recommended that 97.3% of foot rot cases, 95.5% of digital dermatitis cases and 92.3% of sole ulcer cases be treated. The main contributor to the total cost per case of sole ulcer was milk loss (38%), treatment cost for digital dermatitis (42%) and the effect of decreased fertility for foot rot (50%). This model affords versatility as it allows for parameters such as production costs, economic values and disease frequencies to be altered. Therefore, cost estimates are the direct outcome of the farm specific parameters entered into the model. Thus, this model can provide farmers economically optimal guidelines specific to their individual cows suffering from different types of lameness.

The effect of repeated episodes of bacteria-specific clinical mastitis on mortality and culling in Holstein dairy cows

The objective of this study was to estimate the cost of 3 different types of clinical mastitis (CM) (caused by gram-positive bacteria, gram-negative bacteria, and other organisms) at the individual cow level and thereby identify the economically optimal management decision for each type of mastitis. We made modifications to an existing dynamic optimization and simulation model, studying the effects of various factors (incidence of CM, milk loss, pregnancy rate, and treatment cost) on the cost of different types of CM. The average costs per case (US

Optimal insemination and replacement decisions to minimize the cost of pathogen-specific clinical mastitis in dairy cows

) of gram-positive, gram-negative, and other CM were

Evidence of no protection for a recurrent case of pathogen specific clinical mastitis from a previous case

133.73,

Biosecurity practices and the potential for exhibited pigs to consume swill at agricultural shows in Australia

211.03, and

The value of pathogen information in treating clinical mastitis

95.31, respectively. This model provided a more informed decision-making process in CM management for optimal economic profitability and determined that 93.1% of gram-positive CM cases, 93.1% of gram-negative CM cases, and 94.6% of other CM cases should be treated. The main contributor to the total cost per case was treatment cost for gram-positive CM (51.5% of the total cost per case), milk loss for gram-negative CM (72.4%), and treatment cost for other CM (49.2%). The model affords versatility as it allows for parameters such as production costs, economic values, and disease frequencies to be altered. Therefore, cost estimates are the direct outcome of the farm-specific parameters entered into the model. Thus, this model can provide farmers economically optimal guidelines specific to their individual cows suffering from different types of CM.

Economic comparison of common treatment protocols and J5 vaccination for clinical mastitis in dairy herds using optimized culling decisions.

The objective of this study was to estimate the effect of a first and repeated cases of bacteria-specific clinical mastitis (CM) on the risk of mortality and culling in Holstein dairy cows. The pathogens studied were Streptococcus spp., Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., Trueperella pyogenes, others, and no growth on aerobic culture. A total of 50,166 lactations were analyzed from 5 large, high-milk-producing dairy herds in New York State from 2003/2004 to 2011. Generalized linear mixed models with a Poisson error distribution were used to study the effects of parity, month of lactation, CM, calving diseases, pregnancy status, current season, and economic values on the risk of mortality and culling. Among first-lactation cows, the presence of a first CM case generally exposed cows to a greater risk of mortality in the current month (compared with the absence of a first case). This was especially acute with a first case of Klebsiella spp., where cows were 4.5 times more at risk [95% confidence interval (CI): 2.7-7.6] of mortality, and with a first case of E. coli were 3.3 times more at risk (95% CI: 2.5-4.5). In first-parity cows, the risk of culling generally increased with a case of bacteria-specific CM. This was observed among cows with a first case of T. pyogenes [relative risk=10.4 (95% CI: 8.4-12.8)], a first case of Klebsiella spp. [relative risk=6.7 (95% CI: 5.5-8.1)], a first case of Staph. aureus [relative risk=4.8 (95% CI: 2.7-8.4)], a first case of E. coli [relative risk=3.1 (95% CI: 2.7-3.6)], and a third case of Klebsiella spp. [relative risk=5.0 (95% CI: 3.1-8.0)]. In general, the presence of a first or second/third case resulted in cows in parity ≥2 with a greater risk of mortality. This was greatest for cows with a first case of Klebsiella spp. [relative risk=3.7 (95% CI: 3.3-4.3)], followed by a second/third case of Klebsiella spp. [relative risk=3.2 (95% CI: 2.5-4.0)], a first case of E. coli [relative risk=3.0 (95% CI: 2.7-3.3)], and a first case of other CM [relative risk=1.8 (95% CI: 1.6-2.0)]. Among cows of parity ≥2, the risk of culling was greater for cows as they progressed through lactations [i.e., cows in parity 4+ were 2.1 (95% CI: 2.0-2.2) times more likely to be culled compared with cows in lactation 2 (the baseline)]. The risk of culling dependent on the cows characteristics can be easily calculated from the parameter estimates in the provided tables.

Implementing structural equation models to observational data from feedlot production systems

Mastitis is a serious production-limiting disease, with effects on milk yield, milk quality, and conception rate, and an increase in the risk of mortality and culling. The objective of this study was 2-fold: (1) to develop an economic optimization model that incorporates all the different types of pathogens that cause clinical mastitis (CM) categorized into 8 classes of culture results, and account for whether the CM was a first, second, or third case in the current lactation and whether the cow had a previous case or cases of CM in the preceding lactation; and (2) to develop this decision model to be versatile enough to add additional pathogens, diseases, or other cow characteristics as more information becomes available without significant alterations to the basic structure of the model. The model provides economically optimal decisions depending on the individual characteristics of the cow and the specific pathogen causing CM. The net returns for the basic herd scenario (with all CM included) were

Detection and Quantification of Seven Major Serogroups of Shiga Toxin–Producing Escherichia coli on Hides of Cull Dairy, Cull Beef, and Fed Beef Cattle at Slaughter†

507/cow per year, where the incidence of CM (cases per 100 cow-years) was 35.6, of which 91.8% of cases were recommended for treatment under an optimal replacement policy. The cost per case of CM was