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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$) of gram-positive, gram-negative, and other CM were $133.73, $211.03, and $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.

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 cow's characteristics can be easily calculated from the parameter estimates in the provided tables.