Economics of reducing antibiotic usage for pathogen-specific clinical mastitis through genomic selection and disease management.

The recent introduction of the mastitis resistance trait into the US genomic selection index, Lifetime Net Merit 2018 (NM$), is expected to reduce the incidence of pathogen-specific clinical mastitis (PS-CM) incidence in U.S. dairy herds. To maximize the herd performance by reducing the PS-CM incidence, we compared the herd performance of 6 different replacement selection and PS-CM disease management strategies. We used an agent-based dairy simulation model in which the performance of individual animals was affected by the genetic traits included in the NM$. The genetic trends for the sires used affected the 15 yr herd performance. Each animal had a daily underlying base probability of contracting 5 different types of PS-CM (Staphylococcus aureus, Streptococcus dysgalactiae, Strep. uberis, Escherichia coli and Klebsiella) during lactation. On top of this base probability, the genetic and environmental components of the mastitis resistance trait (MAST) determined the actual incidence of PS-CM. Genomic estimated breeding values were simulated for each animal, based on which replacement selection decisions were made. The PS-CM associated milk loss, increased somatic cell count, decreased conception, and increased mortality and culling were accounted for in the simulated genomic estimated breeding values of different correlated production and reproduction traits included in NM$. The 6 different strategies illustrate the effects of replacement selection and PS-CM management decisions on PS-CM incidence, herd antibiotic use (ABU) and herd economics, over the course of 15 yr. Due to the genetic gain in the MAST, the incidence of PS-CM decreased on average by 10% points in 15 yr, which trickled down to overall reduction in herd ABU. Our PS-CM treatment and prevention strategies were assumed to be based on precise information about the 5 different PS-CM causative pathogens. Hence the corresponding ABU further decreased over the course of 15 years, when compared to blanket PS-CM therapies, which used antibiotics for all cases of CM. Our strategies illustrated the fact that herds combining genomic selection and following precise treatment and prevention strategies for PS-CM could reduce the 15-year cumulative ABU against PS-CM significantly. Capitalizing on the genetic gain in NM$ traits, the average profit per cow per year was higher on average by $1209 in year 15 when compared to year 0 for the 6 strategies simulated. We concluded that three decision strategies (genomic selection for NM$, selective therapy for PS-CM, and selective dry cow therapy for PS-CM prevention) when combined can reduce the incidence of PS-CM and the associated ABU, while increasing the profitability of the herd.

Cost benefit analysis of automatic lameness detection systems in dairy herds: A dynamic programming approach.

Epidemiological data establish that lameness is second only to mastitis as the dairy industry's most prevalent and costly animal welfare issue. Using an automatic lameness detection (ALD) system in which continuous, accurate detection is coupled with proper treatment, is key for reducing economic losses due to lameness. It is reasonable to assume that the cost of lameness would vary with its severity. Therefore, our first objective was to estimate the cost of different lameness severity levels as a function of milk production, lameness risk, conception probability, and treatment cost using a dynamic programming (DP) model. Our second objective was to conduct a cost benefit analysis for ALD systems which can reduce production losses through early detection and treatment of lameness, when compared to visual-detection (VD; i.e., performed by humans) systems. The default production loss parameters for the VD system used as inputs to the DP model were either sourced from the literature or were estimated based on data from a field trial. The production loss parameters for the ALD system used as inputs to the DP model were based on extrapolations of parameter values used for the VD system. The profit per present cow per year under assumed expenses and revenues decreased from $426.05 (when lameness incidence was assumed to be 0%) to $389.69 when lameness incidence was 19.5 %. Out of the 19.5 % lameness incidence in our default scenario, 9.8 % were moderate cases and 9.7 % were severe cases. Average cost of lameness was $36.36 at 19.5 % incidence. Average cost of lameness increased with increased incidence and was respectively $82.05, $195.05, and $286.87 at the low, medium, and high incidence scenarios. We used an operational framework which compared the lameness costs between the VD and ALD systems with 25 %, 50 % and 75 % net avoided costs (NAC) for the 10 year lifespan of the ALD system, at default, low, medium and high lameness incidence scenarios. The net return per cow per year from using an ALD system over a VD system was $13, at low incidence and 25 % NAC. The net return per cow per year for the ALD system was as high as $99 at high incidence and 75 % NAC. Out of 351 (3 system prices, 3 system efficiencies, 3 levels of lameness incidence and 13 different herd sizes) scenarios tested, 295 resulted in a net profit within the system lifespan of 10 years, thus justifying the investment in ALD systems.

Does clinical mastitis in the first 100 days of lactation 1 predict increased mastitis occurrence and shorter herd life in dairy cows?

The objectives of this study were to estimate the direct effects of clinical mastitis (CM) occurring in early productive life (defined as the first 100 d of the first lactation) of Holstein dairy cows on the future rate of CM occurrence and on the length of total productive lifetime. Information on CM cases and other data occurring in 55,144 lactations in 24,831 cows in 5 New York State Holstein herds was collected from January 2004 until February 2014. For the first objective, a generalized linear mixed model with a Poisson distribution was used to study the effects of CM cases occurring in the first 100 d of a cow's first lactation, as well as farm indicator and number of days in the cow's lifetime, on the future lifetime rate of CM. Only cows that had completed their productive life [i.e., all had been culled (or sold) or had died; n = 14,440 cows] were included in this analysis. For the second objective, a Cox proportional hazards model was used to study the effects of CM cases occurring in the first 100 d of a cow's first lactation on the length of total productive lifetime. The model was stratified by farm. All 24,831 cows were included in this analysis with right censoring. Cows experienced between 0 and 4 CM cases in the first 100 d of lactation 1. Over their lifetime, cows experienced between 0 and 25 CM cases. During the study period, 10% of all cows died and nearly half of all cows were culled. The average length of productive life, including censored observations, was 2.0 yr after first calving. Compared with cows having no CM cases in the first 100 d of lactation 1, cows with 1 CM case in that time period had a 1.5 times higher rate of total number of CM cases over their lifetime. Cows with 2 (or 3 or more) CM cases in the first 100 d of lactation 1 had a 1.7 times (or 2.6 times) higher rate of total number of CM cases over their lifetime. For each additional CM case occurring in the first 100 d of lactation 1, the hazard rate of culling increased by 34%. Given economic conditions for preferentially culling mastitic cows, the study findings may help farmers make optimal decisions with regard to culling of such cows.

Effects of pathogen-specific clinical mastitis on probability of conception in Holstein dairy cows.

The objective of this study was to estimate the effects of pathogen-specific clinical mastitis (CM), occurring in different weekly intervals before or after artificial insemination (AI), on the probability of conception in Holstein cows. Clinical mastitis occurring in weekly intervals from 6 wk before until 6 wk after AI was modeled. The first 4 AI in a cow's lactation were included. The following categories of pathogens were studied: Streptococcus spp. (comprising Streptococcus dysgalactiae, Streptococcus uberis, and other Streptococcus spp.); Staphylococcus aureus; coagulase-negative staphylococci (CNS); Escherichia coli; Klebsiella spp.; cases with CM signs but no bacterial growth (above the level that can be detected from our microbiological procedures) observed in the culture sample and cases with contamination (≥ 3 pathogens in the sample); and other pathogens [including Citrobacter, yeasts, Trueperella pyogenes, gram-negative bacilli (i.e., gram-negative organisms other than E. coli, Klebsiella spp., Enterobacter, and Citrobacter), Corynebacterium bovis, Corynebacterium spp., Pasteurella, Enterococcus, Pseudomonas, Mycoplasma, Prototheca, and others]. Other factors included in the model were parity (1, 2, 3, 4 and higher), season of AI (winter, spring, summer, autumn), day in lactation of first AI, farm, and other non-CM diseases (retained placenta, metritis, ketosis, displaced abomasum). Data from 90,271 AI in 39,361 lactations in 20,328 cows collected from 2003/2004 to 2011 from 5 New York State dairy farms were analyzed in a generalized linear mixed model with a Poisson distribution. The largest reductions in probability of conception were associated with CM occurring in the week before AI or in the 2 wk following AI. Escherichia coli and Klebsiella spp. had the greatest adverse effects on probability of conception. The probability of conception for a cow with any combination of characteristics may be calculated based on the parameter estimates. These findings may be helpful to farmers in assessing reproduction in their dairy cows for more effective cow management.

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

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 $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 $216.11. The CM cases comprised (incidences, %) Staphylococcus spp. (1.6), Staphylococcus aureus (1.8), Streptococcus spp. (6.9), Escherichia coli (8.1), Klebsiella spp. (2.2), other treated cases (e.g., Pseudomonas; 1.1), other not treated cases (e.g., Trueperella pyogenes; 1.2), and negative culture cases (12.7). The average cost per case, even under optimal decisions, was greatest for Klebsiella spp. ($477), followed by E. coli ($361), other treated cases ($297), and other not treated cases ($280). This was followed by the gram-positive pathogens; among these, the greatest cost per case was due to Staph. aureus ($266), followed by Streptococcus spp. ($174) and Staphylococcus spp. ($135); negative culture had the lowest cost ($115). The model recommended treatment for most CM cases (>85%); the range was 86.2% (Klebsiella spp.) to 98.5% (Staphylococcus spp.). In general, the optimal recommended time for replacement was up to 5 mo earlier for cows with CM compared with cows without CM. Furthermore, although the parameter estimates implemented in this model are applicable to the dairy farms in this study, the parameters may be altered to be specific to other dairy farms. Cow rankings and values based on disease status, pregnancy status, and milk production can be extracted; these provide guidance when determining which cows to keep or cull.

Pathogen-specific effects on milk yield in repeated clinical mastitis episodes in Holstein dairy cows.

The objective of this study was to estimate the effects of clinical mastitis (CM) cases due to different pathogens on milk yield in Holstein cows. The first 3 CM cases in a cow's lactation were modeled. Eight categories of pathogens were included: Streptococcus spp.; Staphylococcus aureus; coagulase-negative staphylococci (CNS); Escherichia coli; Klebsiella spp.; cases with CM signs but no bacterial growth (above the level detectable by our microbiological procedures) observed in the culture sample, and cases with contamination (≥ 3 pathogens in the sample); other pathogens that may be treated with antibiotics (included Citrobacter, Corynebacterium bovis, Enterobacter, Enterococcus, Pasteurella, Pseudomonas; "other treatable"); and other pathogens not successfully treated with antibiotics (Trueperella pyogenes, Mycoplasma, Prototheca, yeasts; "other not treatable"). Data from 38,276 lactations in cows from 5 New York State dairy herds, collected from 2003-2004 until 2011, were analyzed. Mixed models with an autoregressive correlation structure (to account for correlation among the repeated measures of milk yield within a lactation) were estimated. Primiparous (lactation 1) and multiparous (lactations 2 and 3) cows were analyzed separately, as the shapes of their lactation curves differed. Primiparas were followed for up to 48 wk of lactation and multiparas for up to 44 wk. Fixed effects included parity, calving season, week of lactation, CM (type, case number, and timing of CM in relation to milk production cycle), and other diseases (milk fever, retained placenta, metritis, ketosis, displaced abomasum). Herd was modeled as a random effect. Clinical mastitis was more common in multiparas than in primiparas. In primiparas, Streptococcus spp. occurred most frequently as the first case. In multiparas, E. coli was most common as the first case. In subsequent cases, CM cases with no specific growth or contamination were most common in both parity groups. The hazard of CM increased with case number. Mastitic cows were generally higher producers before the CM episode than their nonmastitic herdmates. Milk loss varied with pathogen and case number. In primiparas, the greatest losses were associated with E. coli and "other not treatable" organisms. In multiparas, the greatest losses were associated with Klebsiella spp. and "other not treatable" organisms. Milk loss was not associated with occurrence of CNS. The findings may help farmers to make optimal management decisions for their cows.

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 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.

The effect of recurrent episodes of clinical mastitis caused by gram-positive and gram-negative bacteria and other organisms on mortality and culling in Holstein dairy cows.

The objective of this study was to estimate the effects of recurrent episodes of different types of clinical mastitis (CM) caused by gram-positive (Streptococcus spp., Staphylococcus aureus, Staphylococcus spp.) and gram-negative (Escherichia coli, Klebsiella, Citrobacter, Enterobacter, Pseudomonas) bacteria, and other organisms (Arcanobacterium pyogenes, Mycoplasma, Corynebacterium bovis, yeast, miscellaneous) on the probability of mortality and culling in Holstein dairy cows. Data from 30,233 lactations in cows of 7 dairy farms in New York State were analyzed. Cows were followed for the first 10 mo in lactation, or until death or culling occurred, or until the end of our study period. Generalized linear mixed models with a Poisson error distribution were used to study the effects of recurrent cases of the different types of CM and several other factors (herd, parity, month of lactation, current year and season, profitability, net replacement cost, other diseases) on cows' probability of death (model 1) or being culled (model 2). Primiparous and multiparous cows were modeled separately because they had different risks of mortality and culling and potentially different CM effects on mortality and culling. Approximately 30% of multiparous cows had at least one case of CM in lactation compared with 16.6% of primiparous cows. Multipara also had higher lactational incidence risks of second (10.7%) and third (4.4%) cases than primipara (3.7% and 1.1%, respectively). For primipara, CM increased the probability of death, with each successive case occurring in a month being increasingly lethal. In multipara, gram-negative CM increased the probability of death, especially when the gram-negative case was the first or second CM case in lactation. Primiparous cows with CM were more likely to be culled after CM than if they did not have CM, particularly after a second or third case. In multipara, any type of CM increased the probability of being culled. Gram-negative CM cases were associated with the numerically highest risk of culling.

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

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 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$) 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.

Effects of clinical mastitis caused by gram-positive and gram-negative bacteria and other organisms on the probability of conception in New York State Holstein dairy cows.

The objective of this study was to estimate the effects of different types of clinical mastitis (CM) on the probability of conception in New York State Holstein cows. Data were available on 55,372 artificial inseminations (AI) in 23,695 lactations from 14,148 cows in 7 herds. We used generalized linear mixed models to model whether or not a cow conceived after a particular AI. Independent variables included AI number (first, second, third, fourth), parity, season when AI occurred, farm, type of CM (due to gram-positive bacteria, gram-negative bacteria, or other organisms) in the 6 wk before and after an AI, and occurrence of other diseases. Older cows were less likely to conceive. Inseminations occurring in the summer were least likely to be successful. Retained placenta decreased the probability of conception. Conception was also less likely with each successive AI. The probability of conception associated with the first AI was 0.29. The probability of conception decreased to 0.26, 0.25, and 0.24 for the second, third, and fourth AI, respectively. Clinical mastitis occurring any time between 14 d before until 35 d after an AI was associated with a lower probability of conception; the greatest effect was an 80% reduction associated with gram-negative CM occurring in the week after AI. In general, CM due to gram-negative bacteria had a more detrimental effect on probability of conception than did CM caused by gram-positive bacteria or other organisms. Furthermore, CM had more effect on probability of conception immediately around the time of AI. Additional information about CM (i.e., its timing with respect to AI, and whether the causative agent is gram-positive or gram-negative bacteria, or other organisms) is valuable to dairy personnel in determining why some cows are unable to conceive in a timely manner. These findings are also beneficial for the management of mastitic cows (especially those with gram-negative CM) when mastitis occurs close to AI.

Effects of repeated gram-positive and gram-negative clinical mastitis episodes on milk yield loss in Holstein dairy cows.

The objective of this study was to estimate the effects of recurrent episodes of gram-positive and gram-negative cases of clinical mastitis (CM) on milk production in Holstein dairy cows. We were interested in the severity of repeated cases in general, but also in the severity of the host response as judged by milk production loss when a previous case was caused by a similar or different microorganism. The results were based on data from 7,721 primiparous lactations and 13,566 multiparous lactations in 7 large dairy herds in New York State. The distribution of organisms in the CM cases showed 28.5% gram-positive cases, 31.8% gram-negative cases, 15.0% others, and 24.8% with no organism identified. Mixed models, with a random herd effect and an autoregressive covariance structure to account for repeated measurements, were used to quantify the effect of repeated CM and several other control variables (parity, week of lactation, other diseases) on milk yield. Our data indicated that repeated CM cases showed a very similar milk loss compared with the first case. No reduction of severity was present with increasing count of the CM case. Gram-negative cases had more severe milk loss compared with gram-positive and other cases irrespective of the count of the case in lactation. Milk loss in multipara (primipara) due to gram-negative CM was approximately 304 kg (228 kg) in the 50 d following CM. This loss was approximately 128 kg (133 kg) for gram-positive cases and 92 kg (112 kg) for other cases. The severity of a second case of gram-negative CM was not reduced by previous cases of gram-negative CM in multipara and only slightly less severe in a similar scenario in primipara cows. Similarly, a previous gram-positive case did not reduce severity of a second or third gram-positive case. Hence, our data do not support that immunological memory of previous exposure to an organism in the same generic class provides protection for a next case of CM with an organism in the same class.

Effects of repeated episodes of generic clinical mastitis on mortality and culling in dairy cows.

Bovine clinical mastitis (CM) can be detrimental to a dairy farm's profitability, not only in terms of lost production and treatment costs, but also because of the loss of the cows themselves. Our objective was to estimate the effects of multiple occurrences of generic bovine CM on mortality and culling. We studied 16,145 lactations from 5 large, high-producing dairy herds, with 3,036 first, 758 second, and 288 third CM cases observed in the first 10 mo after calving. Generalized mixed models, with a random herd effect, were used to quantify the effect of CM on mortality and culling. Other control variables included in the models were parity, stage of lactation, and other diseases. Clinical mastitis in the current month significantly increased mortality in all parities. Among primipara, odds ratios and 95% confidence intervals were 5.6 (1.7, 18.0), 23.3 (7.1, 76.2), and 27.8 (3.7, 209.9) for the first, second, and third CM episode, respectively. Among multipara, respective estimates were 9.9 (7.4, 13.2), 12.0 (8.0, 18.0), and 11.5 (6.1, 21.4). Clinical mastitis significantly increased the risk of a cow being culled for a period of at least 2 mo after any CM case. Our findings provide dairy producers with information on mortality and culling associated with CM cases without considering the causative agent, and can also be used for economic analysis of CM management options.

The cost of generic clinical mastitis in dairy cows as estimated by using dynamic programming.

The objective of this study was to estimate the cost of generic clinical mastitis (CM) in high-yielding dairy cows given optimal decisions concerning handling of CM cases. A specially structured optimization and simulation model that included a detailed representation of repeated episodes of CM was used to study the effects of various factors on the cost of CM. The basic scenario was based on data from 5 large herds in New York State. In the basic scenario, 92% of the CM cases were recommended to be treated. The average cost of CM per cow and year in these herds was $71. The average cost of a CM case was $179. It was composed of $115 because of milk yield losses, $14 because of increased mortality, and $50 because of treatment-associated costs. The estimated cost of CM was highly dependent on cow traits: it was highest ($403) in cows with high expected future net returns (e.g., young, high-milk-yielding cows), and was lowest ($3) in cows that were recommended to be culled for reasons other than mastitis. The cost per case of CM was 18% higher with a 20% increase in milk price and 17% lower with a 20% decrease in milk price. The cost per case of CM was affected little by a 20% change in replacement cost or pregnancy rate. Changes in CM incidence, however, resulted from changes in these factors, thus affecting whole-farm profitability. The detailed results obtained from this insemination and replacement optimization model can assist farmers in making CM treatment decisions.

Effect of repeated episodes of generic clinical mastitis on milk yield in dairy cows.

Our objective was to estimate the milk losses associated with multiple occurrences of generic bovine clinical mastitis (CM) within and across lactations. We studied 10,380 lactations from 5 large, high-producing dairy herds that used automatic recording of daily milk yields. Mixed models, with a random herd effect and an autoregressive covariance structure to account for repeated measurements, were used to quantify the effect of CM and other control variables (parity, week of lactation, other diseases) on milk yield. Many cows that developed CM were higher producers than their non-mastitic herdmates before CM occurred. Milk yield began to drop after diagnosis; the greatest loss occurred in the first weeks (up to 126 kg) and then gradually tapered to a constant value approximately 2 mo after CM. Mastitic cows often never recovered their potential yield. First-lactation cows lost 164 kg of milk for the first episode and 198 kg for the second in the 2 mo after CM diagnosis, compared with their potential yield. Among older cows, this estimate was 253 kg for the first, 238 kg for the second, and 216 kg for the third CM case. A cow that had 1 or more CM episodes in her previous lactation produced 1.2 kg/d less milk over the whole current lactation (95% confidence interval: 0.6, 1.7) than a cow without CM in her previous lactation. These findings provide dairy producers with information on the average milk loss associated with CM cases without considering the causative agent, and can be used for economic analysis.

Effect of pathogen-specific clinical mastitis on herd life in two New York State dairy herds.

The objective of this study was to estimate the effects of clinical mastitis (CM) (both with and without specific pathogen identification) occurring in different stages of lactation on length of herd life in two New York State dairy farms. The 2,697 cows in the study were followed for one lactation (the first-occurring one on or after 1 October 1999), until it ended because of a new lactation, culling, or end of study (31 March 2001 in one farm; 31 July 2001 in the other). A Cox proportional hazards model with time-dependent covariates, in SAS((R)), was used to measure, within a lactation, the effect of the first occurrence of CM (without specific pathogen identification) occurring 1--7, 8--66, 67--100, 101--225, or >or=226 days in milk (DIM), on how long cows remained in the herd. For the first occurrence of CM due to Streptococcus spp., Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., and 'no pathogen isolated', the intervals were before and after the median DIM of first occurrence of each pathogen. There were too few cases due to Arcanobacterium pyogenes, and 'other pathogens grouped together' to split into intervals, so they were modeled as binary variables, i.e. as they occurred. CM was modeled using time-dependent covariates, to account for its differing effects throughout lactation on culling. Other variables controlled for were herd, parity, calving season, and other significant diseases. In the dataset, the lactational incidence risk of the first occurrence of CM was 18.2%; 20.0% of the cows did not survive the lactation that was studied. The overall annual culling percentage for both herds during the study period (including all cows, whether eligible for the study or not) was 35.6%. For cows with CM without pathogen identification, their highest hazard ratio (HR) of culling occurred from 67 to 100 DIM. All of the pathogens modeled markedly reduced herd life. On average over the entire lactation, cows with Staphylococcus spp. CM had the highest HRs for culling, although there were no significant differences among pathogens (at p=0.0018 (reflecting 28 pairwise comparisons)). For early-occurring (before median DIM of first occurrence) S. aureus CM, the daily rate of change of the HR of culling increased over time. The HRs for culling were particularly high for late-occurring (after median DIM of first occurrence) E. coli and Klebsiella spp. CM early in the interval, but the daily rate of change of the hazard of culling for these two pathogens decreased sharply over time. Treating CM as time-dependent therefore allowed us to measure in greater detail, its varying effects (of when it occurred) on herd life.

Effect of pathogen-specific clinical mastitis on milk yield in dairy cows.

Our objective was to estimate the effects of the first occurrence of pathogen-specific clinical mastitis (CM) on milk yield in 3071 dairy cows in 2 New York State farms. The pathogens studied were Streptococcus spp.,Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., Arcanobacterium pyogenes, other pathogens grouped together, and "no pathogen isolated." Data were collected from October 1999 to July 2001. Milk samples were collected from cows showing signs of CM and were sent to the Quality Milk Production Services laboratory at Cornell University for microbiological culture. The SAS statistical procedure PROC MIXED, with an autoregressive covariance structure, was used to quantify the effect of CM and several other control variables (herd, calving season, parity, month of lactation, J-5 vaccination status, and other diseases) on weekly milk yield. Separate models were fitted for primipara and multipara, because of the different shapes of their lactation curves. To observe effects of mastitis, milk weights were divided into several periods both pre- and postdiagnosis, according to when they were measured in relation to disease occurrence. Another category contained cows without the type of CM being modeled. Because all pathogens were modeled simultaneously, a control cow was one without CM. Among primipara, Staph. aureus, E. coli, Klebsiella spp., and "no pathogen isolated" caused the greatest losses. Milk yield generally began to drop 1 or 2 wk before diagnosis; the greatest loss occurred immediately following diagnosis. Mastitic cows often never recovered their potential yield. Among older cows, Streptococcus spp., Staph. aureus, A. pyogenes, E. coli, and Klebsiella spp. caused the most significant losses. Many multipara that developed CM were actually higher producers before diagnosis than their nonmastitic herd-mates. As in primipara, milk yield in multipara often began to decline shortly before diagnosis; the greatest loss occurred immediately following diagnosis. Milk loss persisted until at least 70 d after diagnosis for Streptococcus spp., Klebsiella spp., and A. pyogenes. The tendency for higher producing cows to contract CM may mask its impact on cow health and production. These findings provide dairy producers with more information on which pathogen-specific CM cases should receive treatment and how to manage these cows, thereby reducing CM impact on cow well being and profitability.

Effect of clinical mastitis on the lactation curve: a mixed model estimation using daily milk weights.

The objective of this study was to estimate the milk production losses associated with clinical mastitis using mixed linear models and correlation structures that have not been available previously. Data used included computer-recorded daily milk yields and detailed and accurate recordings of clinical mastitis cases. Two commercial Holstein dairy farms in New York State participated in the study, one with 650 lactating cows and another that began the study with 830 lactating cows and increased to 1120 cows by the end of the study. Cows on both farms were housed in free stall barns and milked 3 times daily in milking parlors. Electrical conductivity was used as a diagnostic aid for clinical mastitis on both farms. Date of clinical onset was recorded for every episode of clinical mastitis as well as for 8 other diseases defined using standardized case definitions (dystocia, milk fever, retained placenta, metritis, ketosis, displaced abomasum, lameness, and cystic ovarian disease) during the study period of October 1, 1999 to July 31, 2001. The mixed linear model for explaining variation in the outcome variable daily milk yield relative to non-mastitic herdmates found the terms for all 9 diseases studied, including clinical mastitis, significant. The model with an autoregressive correlation structure was preferred based on -2 * log likelihood, Akaike's information criterion, and Bayesian information criterion as well as savings in degrees of freedom. Separate analyses were run for first lactation cows and for second-plus lactation cows because their lactation curves were shaped differently. Adjusting for the effects of the other 8 diseases, milk production loss from clinical mastitis during the whole lactation was estimated as approximately 598 kg for second-plus lactation cows. However, cows that contracted mastitis had a daily production advantage of 2.6 kg over their herdmates until they contracted the disease. When compared with this potentially higher milk production, the total loss from clinical mastitis was estimated as 1181 kg.

Optimizing replacement of dairy cows: modeling the effects of diseases.

We modified an existing dairy management decision model by including economically important dairy cattle diseases, and illustrated how their inclusion changed culling recommendations. Nine common diseases having treatment and veterinary costs, and affecting milk yield, fertility and survival, were considered important in the culling decision process. A sequence of stages was established during which diseases were considered significant: mastitis and lameness, any time during lactation; dystocia, milk fever and retained placenta, 0-4 days of lactation; displaced abomasum, 5-30 days; ketosis and metritis, 5-60 days; and cystic ovaries, 61-120 days. Some diseases were risk factors for others. Baseline incidences and disease effects were obtained from the literature. The effects of various disease combinations on milk yield, fertility, survival and economics were estimated. Adding diseases into the model did not increase voluntary or total culling rate. However, diseased animals were recommended for culling much more than healthy cows, regardless of parity or production level. Cows in the highest production level were not recommended for culling even if they contracted a disease. The annuity per cow decreased and herdlife increased when diseases were in the model. Higher replacement cost also increased herdlife and decreased when diseases were in the model. Higher replacement cost also increased herdlife and decreased the annuity and voluntary culling rate.

Censoring in survival analysis: a simulation study of the effect of milk yield on conception.

Survival-analysis methods often are used to analyze data from dairy herds where the outcome of interest is the interval from calving to conception. The purpose of this study was to determine whether an association between milk yield and culling biases the estimation of the effect of milk yield on conception. This was done by simulating four different scenarios modeling dairy-cattle milk yield and reproductive performance with known relationships among study factors. Cox's proportional-hazards model was used to analyze the effect of milk yield on days open under the following four scenarios: (1) no association between milk yield and culling or between milk yield and conception; (2) association between milk yield and culling only; (3) association between milk yield and conception only; (4) associations between milk yield and both culling and conception. The analyses also were repeated for data sets with an association between milk yield and culling, but with probabilities of culling ranging from 0.01 to 0.4. An effect of milk production on culling appeared to cause a small increase in the parameter estimates for the association of milk yield and days open - particularly when the probability of culling was high. The effect of high milk production on median days open (as estimated by survival functions) changed by 2 to 4 days when an association between milk yield and culling was programmed in the simulated data sets.