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.

Ranking disease control strategies with stochastic outcomes.

This paper explains how the methodologies of first and second order stochastic dominance, and expected utility using specific risk preferences, can be applied to epidemiology when choosing among control strategies that have stochastic outcomes. We provide a step-by-step guide on how epidemiologists can rank a number of control strategies based on their distribution of estimated benefits. We also explain how the expected utility model and decision maker's risk preferences can be used to select between outcomes when none stochastically dominates. To illustrate these techniques, we show the ranking of various control strategies for a dairy herd endemically infected with Mycobacterium avium subs. paratuberculosis (MAP) and mastitis, and explain how decision maker's risk preferences affect the ranking.

Economics of reducing antibiotic usage for clinical mastitis and metritis through genomic selection.

Antibiotics use (ABU) in animal agriculture has been implicated in the emergence of antibiotic resistance, a global public health threat. Economically justifiable antibiotic reduction strategies can motivate farmers to reduce ABU for clinical mastitis (CM) and metritis, the most common reasons for ABU on dairy farms. Our objective was to quantify the reduction in incidence of CM, metritis, and ABU, and the herd performance of a representative US herd that uses genomic selection for Lifetime Net Merit 2018 (NM$) selection index, compared with genetic selection based only on the mastitis (MAST) or metritis resistance (METR) trait or a health trait subindex (HTH$). A stochastic dynamic simulation model of a 1,000-cow herd with multi-trait genetics for 19 correlated traits included in the NM$ affected the performance of animals. The incidence of CM and metritis for each animal was affected by the genetic and environmental components of the MAST or METR, along with a standard phenotypic function that calculated the daily underlying herd probability to contract CM or metritis. Selection decisions were made based on genomic estimated breeding values of the traits of interest. A strategy named AI-NM$ based decisions on the NM$ trait so that the correlated genetic trends in MAST and METR are improved. Three other strategies named AI-MAST, AI-METR, and AI-HTH$ maximized respectively MAST, METR, and HTH$ genetic merit, but with a tradeoff in NM$ genetic merit. The cumulative true breeding values (TBV) of NM$ for 15 yr showed a difference of $4,947 per cow between the AI-NM$ (best strategy for NM$) and AI-METR (worst strategy for NM$). However, the 15-yr cumulative TBV of MAST was 26.50 percentage points (PP) higher in AI-MAST, and 18.5 PP higher for METR in AI-METR, compared with AI-NM$. As a result, the 15-yr cumulative phenotypic CM and metritis incidence was respectively 94.03 PP and 58 PP lower in AI-MAST and AI-METR compared with AI-NM$. Therefore the corresponding 15-yr cumulative ABU decreased by 42% in AI-MAST and by 53% in AI-METR. We found that AI-MAST had the lowest CM incidence across the 15 yr, whereas AI-METR had the lowest incidence of metritis and the smallest total ABU for 15 yr. To achieve the lowest incidence of CM, metritis, and ABU strategies AI-MAST, AI-METR, and AI-HTH$ had to incur 15-yr discounted cumulative losses per cow of $1,486, $1,434, and $1,130, respectively, compared with AI-NM$. Hence, AI-NM$ had the best financial performance, despite having slightly higher incidence of CM, metritis, and ABU.

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.

Comparing technical efficiency of farms with an automatic milking system and a conventional milking system.

Changing from a conventional milking system (CMS) to an automatic milking system (AMS) necessitates a new management approach and a corresponding change in labor tasks. Together with labor savings, AMS farms have been found to have higher capital costs, primarily because of higher maintenance costs and depreciation. Therefore, it is hypothesized that AMS farms differ from CMS farms in capital:labor ratio and possibly their technical efficiency, at least during a transition learning period. The current study used actual farm accounting data from dairy farms in the Netherlands with an AMS and a CMS to investigate the empirical substitution of capital for labor in the AMS farms and to determine if the technical efficiency of the AMS farms differed from the CMS farms. The technical efficiency estimates were obtained with data envelopment analysis. The 63 AMS farms and the 337 CMS farms in the data set did not differ in general farm characteristics such as the number of cows, number of hectares, and the amount of milk quota. Farms with AMS have significantly higher capital costs (€12.71 per 100 kg of milk) than CMS farms (€10.10 per 100 kg of milk). Total labor costs and net outputs were not significantly different between AMS and CMS farms. A clear substitution of capital for labor with the adoption of an AMS could not be observed. Although the AMS farms have a slightly lower technical efficiency (0.76) than the CMS farms (0.78), a significant difference in these estimates was not observed. This indicates that the farms were not different in their ability to use inputs (capital, labor, cows, and land) to produce outputs (total farm revenues). The technical efficiency of farms invested in an AMS in 2008 or earlier was not different from the farms invested in 2009 or 2010, indicating that a learning effect during the transition period was not observed. The results indicate that the economic performance of AMS and CMS farms are similar. What these results show is that other than higher capital costs, the use of AMS rather than a CMS does not affect farm efficiency and that the learning costs to use an AMS are not present as measured by any fall in technical efficiency.

Economic analysis of Mycobacterium avium subspecies paratuberculosis vaccines in dairy herds.

Johne's disease, or paratuberculosis, is a chronic infectious enteric disease of ruminants, caused by infection with Mycobacterium avium ssp. paratuberculosis (MAP). Given the absence of a fail-safe method of prevention or a cure, Johne's disease can inflict significant economic loss on the US dairy industry, with an estimated annual cost of over $200 million. Currently available MAP control strategies include management measures to improve hygiene, culling MAP serologic- or fecal-positive adult cows, and vaccination. Although the 2 first control strategies have been reported to be effective in reducing the incidence of MAP infection, the changes in herd management needed to conduct these control strategies require significant effort on the part of the dairy producer. On the other hand, vaccination is relatively simple to apply and requires minor changes in herd management. Despite these advantages, only 5% of US dairy operations use vaccination to control MAP. This low level of adoption of this technology is due to limited information on its cost-effectiveness and efficacy and some important inherent drawbacks associated with current MAP vaccines. This study investigates the epidemiological effect and economic values of MAP vaccines in various stages of development. We create scenarios for the potential epidemiological effects of MAP vaccines, and then estimate economically justifiable monetary values at which vaccines become economically beneficial to dairy producers such that a net present value (NPV) of a farm's net cash flow can be higher than the NPV of a farm using no control or alternative nonvaccine controls. Any vaccination with either low or high efficacy considered in this study yielded a higher NPV compared with a no MAP control. Moreover, high-efficacy vaccines generated an even higher NPV compared with alternative controls, making vaccination economically attractive. Two high-efficacy vaccines were particularly effective in MAP control and NPV maximization. One was a high-efficacy vaccine that reduced susceptibility to MAP infection. The other was a high-efficacy vaccine that had multiple efficacies on the dynamics of MAP infection and disease progress. Only one high-efficacy vaccine, in which the vaccine is targeted at reducing MAP shedding and the number of clinical cases, was not economically beneficial to dairy producers compared with an alternative nonvaccine control, when herds were highly infected with MAP.

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.

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.

Determining the amount of rumen-protected methionine supplement that corresponds to the optimal levels of methionine in metabolizable protein for maximizing milk protein production and profit on dairy farms.

The profitability of feeding rumen-protected Met (RPMet) sources to produce milk protein was estimated using a 2-step procedure: First, the effect of Met in metabolizable protein (MP) on milk protein production was estimated by using a quadratic Box-Cox functional form. Then, using these estimation results, the amounts of RPMet supplement that corresponded to the optimal levels of Met in MP for maximizing milk protein production and profit on dairy farms were determined. The data used in this study were modified from data used to determine the optimal level of Met in MP for lactating cows in the Nutrient Requirements of Dairy Cattle (NRC, 2001). The data used in this study differ from that in the NRC (2001) data in 2 ways. First, because dairy feed generally contains 1.80 to 1.90% Met in MP, this study adjusts the reference production value (RPV) from 2.06 to 1.80 or 1.90%. Consequently, the milk protein production response is also modified to an RPV of 1.80 or 1.90% Met in MP. Second, because this study is especially interested in how much additional Met, beyond the 1.80 or 1.90% already contained in the basal diet, is required to maximize farm profits, the data used are limited to concentrations of Met in MP above 1.80 or 1.90%. This allowed us to calculate any additional cost to farmers based solely on the price of an RPMet supplement and eliminated the need to estimate the dollar value of each gram of Met already contained in the basal diet. Results indicated that the optimal level of Met in MP for maximizing milk protein production was 2.40 and 2.42%, where the RPV was 1.80 and 1.90%, respectively. These optimal levels were almost identical to the recommended level of Met in MP of 2.40% in the NRC (2001). The amounts of RPMet required to increase the percentage of Met in MP from each RPV to 2.40 and 2.42% were 21.6 and 18.5 g/d, respectively. On the other hand, the optimal levels of Met in MP for maximizing profit were 2.32 and 2.34%, respectively. The amounts of RPMet required to increase the percentage of Met in MP from each RPV to 2.32 and 2.34% were 18.7 and 15.6 g/d, respectively. In each case, the additional daily profit per cow was estimated to be $0.38 and $0.29. These additional profit estimates were $0.02 higher than the additional profit estimates for maximizing milk protein production.

Dairy farm cost efficiency.

A stochastic cost equation was estimated for US dairy farms using national data from the production year 2000 to determine how farmers might reduce their cost of production. Cost of producing a unit of milk was estimated into separate frontier (efficient) and inefficiency components, with both components estimated as a function of management and causation variables. Variables were entered as impacting the frontier component as well as the efficiency component of the stochastic curve because a priori both components could be impacted. A factor that has an impact on the cost frontier was the number of hours per day the milking facility is used. Using the milking facility for more hours per day decreased frontier costs; however, inefficiency increased with increased hours of milking facility use. Thus, farmers can decrease costs with increased utilization of the milking facility, but only if they are efficient in this strategy. Parlors compared with stanchions used for milking did not decrease frontier costs, but decreased costs because of increased efficiency, as did the use of a nutritionist. Use of rotational grazing decreased frontier costs but also increased inefficiency. Older farmers were less efficient.

Profitability of grazing versus mechanical forage harvesting on New York dairy farms.

The profitability of rotational grazing versus mechanical harvesting of forages was estimated using data from 237 nongrazing and 57 grazing farms participating in the New York farm business summary program in the year 2000. The objective was to perform an empirical comparison of the profitability of grazing versus mechanical forage harvesting systems. A regression analysis technique that controls for treatment selection bias is used to determine the impact of grazing on the rate of return on assets. This is accomplished by joint maximum likelihood estimation of a probit adoption function and a profit function. The results indicate that treatment selection does not have an important impact on the estimate of the profitability of grazing. There were wide ranges and overlap of profitability among herds using the two systems. However, other things equal, farmers utilizing grazing systems were at least if not more profitable than farmers not using grazing systems. After controlling for the factors influencing the decision to graze, we found that herd size, rate of milk production per cow, and prices received for milk have a strong positive impact on profitability. Farmers who perceive potential lifestyle benefits that might be obtained by implementing a grazing system likely do not have to pay an income penalty for adopting a grazing system.