Effects of pathogen-specific clinical mastitis occurrence in the first 100 days of lactation 1 on future mastitis occurrence in Holstein dairy cows: An observational study.

The objective of this observational study was to estimate effects of clinical mastitis (CM) cases caused by different pathogens (Streptococcus spp., Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., and CM cases with no growth) occurring in the first 100 d in lactation 1, of a dairy cow on the future rate of occurrence of different types of CM during a cow's full lifetime. The outcomes were occurrence of Streptococcus spp., Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., and CM cases with no growth, after the first 100 d of lactation 1, until a cow's removal through death or sale in that or a subsequent lactation. Data, including information on CM cases, milk production, and event dates (including death or sale dates), were collected from 14,440 cows in 5 New York State Holstein herds from January 2004 until February 2014. Generalized linear mixed models with a Poisson distribution and log link function were fit for each pathogen. The individual cow was the unit of analysis. Escherichia coli was a predictor of future occurrence of E. coli, Klebsiella spp., and CM cases with no growth. Early-occurring Klebsiella spp. was a predictor of future cases of Klebsiella spp. Cases with no growth were predictors of future occurrence of Staphylococcus spp., E. coli, Klebsiella spp., and cases with no growth. Thus, E. coli and cases with no growth occurring early in lactation 1 appear to be consistent risk factors for future cases of CM, whether cases with the same pathogen or a different pathogen. In this study, farm effects on later pathogen occurrence differed somewhat, so treatment protocol and culling strategy may play a role in the findings. Nevertheless, the findings may help farmers in managing young cows with CM in early productive life, especially those with E. coli or cases with no growth, in that they may be more susceptible to future CM cases in their later productive life, thus meriting closer attention.

Association of pathogen-specific clinical mastitis in the first 100 days of first lactation with productive lifetime: An observational study comparing competing risks models for death and sale with the Cox model.

The objective of this observational study was to study the association between clinical mastitis (CM) (Streptococcus spp., Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., cases with other treated or other not treated organisms, CM without growth) occurring in a dairy cow's first 100 days (d) of her first lactation and her total productive lifetime, ending in death or sale (for slaughter). Data were collected from 24,831 cows in 5 New York Holstein herds from 2004 to 2014. Two analytical approaches were compared. First, removals (death, sale) were treated as competing events in separate survival analyses, in proportional subdistribution hazards models. In one, death was coded as the event of interest and sale as the competing event; in another, sale was the event of interest and death the competing event. Second, traditional survival analysis (Cox proportional hazards) was conducted. In all models, the time variable was number of days from date of first calving until event (death or sale) date; if the cow was alive at study end, she was censored. Models were stratified by herd. Ten percent of cows died; 48.4 % were sold. In the competing risks analysis, E. coli and CM without growth were associated with death; the former with an increased hazard rate of death, the latter with a lower one. Streptococcus spp., Staph. aureus, Klebsiella spp., cases with other treated or untreated organisms, and CM without growth were associated with higher hazard rates of sale. The Cox proportional hazards model's hazard rates were higher than those in the competing risks model in which death was the event of interest, and resembled those in the model in which sale was the event of interest. Four additional Cox models, omitting dead or sold cows, or censoring each, were also fitted; hazard ratios were similar to the above models. Proportional subdistribution hazards models were appropriate due to competing risks (death, sale); they produce less-biased estimates. A study limitation is that while proportional subdistribution hazards models were appropriate, they have the illogical feature of keeping subjects at risk for the event of interest even after experiencing the competing event. This is, however, necessary in estimating cumulative incidence functions. Another limitation concerns pathogen variability among study farms, implying that CM decisions are farm-specific. Misclassification of 'dead' vs. 'sold' cows was also possible. Nevertheless, the findings may help in optimizing management of cows contracting specific types of CM early in productive lifetime.

System Economic Costs of Antibiotic Use Elimination in the US Beef Supply Chain.

There is consumer pressure on the US beef cattle industry to minimize antibiotic use (ABU) in order to aid in the global antimicrobial resistance mitigation efforts. Our objective was to estimate the economic costs of ABU constraints in a conceptual US integrated beef supply chain (IBSC) to aid the beef industry in mitigating the ever-increasing risk of antimicrobial resistance, by reducing their ABU. An IBSC network model was developed and differentiated into 37 different nodes of production. Each node could only raise a specific type of animals, differentiated based on the production technique and animal health status. The cost, as well as the weight gain coefficient, was estimated for each node, using an IBSC cost of production model. Linear programming solutions to this network model provided the least cost path of beef supply through the system, under various ABU constraints. The cost as well as weight gain coefficient of the 37 nodes, initial supply of 28.5 million calves weighing 0.65 million metric tons, and final demand of 16.14 million metric tons of slaughter-ready fed cattle were used as inputs/constraints to the three different linear programming scenarios, with different ABU constraints. Our first scenario, which placed no constraint on ABU, estimated that the minimum total economic cost to meet the final beef demand was $38.6 billion. The optimal solution was to use only the high health status calves for beef production. Because low health calves occur in the beef system, our second scenario required all the calves irrespective of their health status to be used, which increased the system cost to $41.5 billion. Thus, the value of only producing high health status calves is $2.9 billion. Our third scenario, which restricted feedlots from using antibiotics even for low health calves, incurred a total cost of $41.9 billion for antibiotic-free beef production. We concluded that the additional cost of $367 million for implementing antibiotic-free beef production is relatively low, ~0.90% of the minimum cost incurred for the conventional beef supply chain (model 2 cost of $41.5 billion). However, a much higher cost savings is obtained by producing only high health status calves.

Bull efficiency using dairy genetic traits.

Dairy bulls are evaluated using progeny data and genomic testing to determine the quantity of specific traits that they will pass to their daughters. Some bulls excel in some traits but not others. Specifying these various traits as outputs, with the single input of insemination, technical, revenue, allocative, and profit efficiency of bulls available for artificial insemination are estimated using Free Disposal Hull. Although bulls generally are highly technically efficient, because only high performing bull semen is offered for sale, bulls are less revenue, allocative and profit efficient. These efficiencies are relative to peer bulls and can be updated as new bulls become available.

Mastitis risk effect on the economic consequences of paratuberculosis control in dairy cattle: A stochastic modeling study.

The benefits and efficacy of control programs for herds infected with Mycobacterium avium subsp. paratuberculosis (MAP) have been investigated under various contexts. However, most previous research investigated paratuberculosis control programs in isolation, without modeling the potential association with other dairy diseases. This paper evaluated the benefits of MAP control programs when the herd is also affected by mastitis, a common disease causing the largest losses in dairy production. The effect of typically suggested MAP controls were estimated under the assumption that MAP infection increased the rate of clinical mastitis. We evaluated one hundred twenty three control strategies comprising various combinations of testing, culling, and hygiene, and found that the association of paratuberculosis with mastitis alters the ranking of specific MAP control programs, but only slightly alters the cost-benefit difference of particular MAP control components, as measured by the distribution of net present value of a representative U.S. dairy operation. In particular, although testing and culling for MAP resulted in a reduction in MAP incidence, that control led to lower net present value (NPV) per cow. When testing was used, ELISA was more economically beneficial than alternative testing regimes, especially if mastitis was explicitly modeled as more likely in MAP-infected animals, but ELISA testing was only significantly associated with higher NPV if mastitis was not included in the model at all. Additional hygiene was associated with a lower NPV per cow, although it lowered MAP prevalence. Overall, the addition of an increased risk of mastitis in MAP-infected animals did not change model recommendations as much as failing to consider.

Assessment of the bovine tuberculosis elimination protocol in the United States.

In this study, we analyzed the performance of the USDA's bovine tuberculosis (bTB) elimination protocol in a 1,000-cow closed dairy herd using an agent-based simulation model under different levels of initial bTB infection. We followed the bTB test sensitivity and specificity values used by the USDA in its model assessment. We estimated the net present value over a 20-yr horizon for a bTB-free milking herd and for bTB-infected herds following the USDA protocol. We estimated the expected time to identify the infection in the herd once it is introduced, its elimination time, the reproductive number (R0), and effective reproduction number (Re) under the USDA protocol. The optimal number of consecutive negative whole-herd tests (WHT) needed to declare a herd bTB-free with a 95% confidence under different bTB prevalence levels was derived. Our results support the minimum number of consecutive negative WHT required by the USDA protocol to declare a herd bTB-free; however, the number of consecutive negative WHT needed to eliminate bTB in a herd depends on the sensitivity and specificity of the tests. The robustness of the protocol was analyzed under conservative bTB test parameters from the literature. The cost of implementing the USDA protocol when 1 infected heifer is introduced in a 1,000-cow dairy herd is about $1,523,161. The average time until detection and the time required to eliminate bTB-infected animals from the herd, after 1 occult animal is introduced in the herd, were 735 and 119 d, respectively.

An agent-based model evaluation of economic control strategies for paratuberculosis in a dairy herd.

This paper uses an agent-based simulation model to estimate the costs associated with Mycobacterium avium ssp. paratuberculosis (MAP), or Johne's disease, in a milking herd, and to determine the net benefits of implementing various control strategies. The net present value (NPV) of a 1,000-cow milking herd is calculated over 20 yr, parametrized to a representative US commercial herd. The revenues of the herd are generated from sales of milk and culled animals. The costs include all variable and fixed costs necessary to operate a representative 1,000-cow milking herd. We estimate the NPV of the herd with no MAP infection, under an expected endemic infection distribution with no controls, and under an expected endemic infection distribution with various controls. The initial number of cows in a herd with an endemic MAP infection is distributed as 75% susceptible, 13% latent, 9% low MAP shedding, and 3% high MAP shedding. Control strategies include testing using ELISA and fecal culture tests and culling of cows that test positive, and culling based on observable milk production decrease. Results show that culling cows based on test results does not increase the herd's NPV and in most cases decreases NPV due to test costs as well as false positives and negatives with their associated costs (e.g., culling healthy cows and keeping infected cows). Culling consistently low producing cows when MAP is believed to be present in the herd produces higher NPV over the strategy of testing and culling MAP infected animals, and over the case of no MAP control.

Optimally achieving milk bulk tank somatic cell count thresholds.

High somatic cell count in milk leads to reduced shelf life in fluid milk and lower processed yields in manufactured dairy products. As a result, farmers are often penalized for high bulk tank somatic cell count or paid a premium for low bulk tank somatic cell count. Many countries also require all milk from a farm to be lower than a specified regulated somatic cell count. Thus, farms often cull cows that have high somatic cell count to meet somatic cell count thresholds. Rather than naïvely cull the highest somatic cell count cows, a mathematical programming model was developed that determines the cows to be culled from the herd by maximizing the net present value of the herd, subject to meeting any specified bulk tank somatic cell count level. The model was applied to test-day cows on 2 New York State dairy farms. Results showed that the net present value of the herd was increased by using the model to meet the somatic cell count restriction compared with naïvely culling the highest somatic cell count cows. Implementation of the model would be straightforward in dairy management decision software.

The value of pathogen information in treating clinical mastitis.

The objective of this study was to determine the economic value of obtaining timely and more accurate clinical mastitis (CM) test results for optimal treatment of cows. Typically CM is first identified when the farmer observes recognisable outward signs. Further information of whether the pathogen causing CM is Gram-positive, Gram-negative or other (including no growth) can be determined by using on-farm culture methods. The most detailed level of information for mastitis diagnostics is obtainable by sending milk samples for culture to an external laboratory. Knowing the exact pathogen permits the treatment method to be specifically targeted to the causation pathogen, resulting in less discarded milk. The disadvantages are the additional waiting time to receive test results, which delays treating cows, and the cost of the culture test. Net returns per year (NR) for various levels of information were estimated using a dynamic programming model. The Value of Information (VOI) was then calculated as the difference in NR using a specific level of information as compared to more detailed information on the CM causative agent. The highest VOI was observed where the farmer assumed the pathogen causing CM was the one with the highest incidence in the herd and no pathogen specific CM information was obtained. The VOI of pathogen specific information, compared with non-optimal treatment of Staphylococcus aureus where recurrence and spread occurred due to lack of treatment efficacy, was $20.43 when the same incorrect treatment was applied to recurrent cases, and $30.52 when recurrent cases were assumed to be the next highest incidence pathogen and treated accordingly. This indicates that negative consequences associated with choosing the wrong CM treatment can make additional information cost-effective if pathogen identification is assessed at the generic information level and if the pathogen can spread to other cows if not treated appropriately.

The effect of bovine somatotropin on the cost of producing milk: Estimates using propensity scores.

Annual farm-level data from New York dairy farms from the years 1994 through 2013 were used to estimate the cost effect from bovine somatotropin (bST) using propensity score matching. Cost of production was computed using the whole-farm method, which subtracts sales of crops and animals from total costs under the assumption that the cost of producing those products is equal to their sales values. For a farm to be included in this data set, milk receipts on that farm must have comprised 85% or more of total receipts, indicating that these farms are primarily milk producers. Farm use of bST, where 25% or more of the herd was treated, ranged annually from 25 to 47% of the farms. The average cost effect from the use of bST was estimated to be a reduction of $2.67 per 100 kg of milk produced in 2013 dollars, although annual cost reduction estimates ranged from statistical zero to $3.42 in nominal dollars. Nearest neighbor matching techniques generated a similar estimate of $2.78 in 2013 dollars. These cost reductions estimated from the use of bST represented a cost savings of 5.5% per kilogram of milk produced. Herd-level production increase per cow from the use of bST over 20 yr averaged 1,160 kg.

Efficiency of dairy farms participating and not participating in veterinary herd health management programs.

This paper compares farm efficiencies between dairies who were participating in a veterinary herd health management (VHHM) program with dairies not participating in such a program, to determine whether participation has an association with farm efficiency. In 2011, 572 dairy farmers received a questionnaire concerning the participation and execution of a VHHM program on their farms. Data from the questionnaire were combined with farm accountancy data from 2008 through 2012 from farms that used calendar year accounting periods, and were analyzed using Stochastic Frontier Analysis (SFA). Two separate models were specified: model 1 was the basic stochastic frontier model (output: total revenue; input: feed costs, land costs, cattle costs, non-operational costs), without explanatory variables embedded into the efficiency component of the error term. Model 2 was an expansion of model 1 which included explanatory variables (number of FTE; total kg milk delivered; price of concentrate; milk per hectare; cows per FTE; nutritional yield per hectare) inserted into the efficiency component of the joint error term. Both models were estimated with the financial parameters expressed per 100 kg fat and protein corrected milk and per cow. Land costs, cattle costs, feed costs and non-operational costs were statistically significant and positive in all models (P<0.01). Frequency distributions of the efficiency scores for the VHHM dairies and the non-VHHM dairies were plotted in a kernel density plot, and differences were tested using the Kolmogorov-Smirnov two-sample test. VHHM dairies had higher total revenue per cow, but not per 100 kg milk. For all SFA models, the difference in distribution was not statistically different between VHHM dairies and non-VHHM dairies (P values 0.94, 0.35, 0.95 and 0.89 for the basic and complete model per 100 kg fat and protein corrected milk and per cow respectively). Therefore we conclude that with our data farm participation in VHHM is not related to overall farm efficiency.

Minimum cost to control bovine tuberculosis in cow-calf herds.

Bovine tuberculosis (bTB) outbreaks in US cattle herds, while rare, are expensive to control. A stochastic model for bTB control in US cattle herds was adapted to more accurately represent cow-calf herd dynamics and was validated by comparison to 2 reported outbreaks. Control cost calculations were added to the model, which was then optimized to minimize costs for either the farm or the government. The results of the optimization showed that test-and-removal costs were minimized for both farms and the government if only 2 negative whole-herd tests were required to declare a herd free of infection, with a 2-3 month testing interval. However, the optimal testing interval for governments was increased to 2-4 months if the model was constrained to reject control programs leading to an infected herd being declared free of infection. Although farms always preferred test-and-removal to depopulation from a cost standpoint, government costs were lower with depopulation more than half the time in 2 of 8 regions. Global sensitivity analysis showed that indemnity costs were significantly associated with a rise in the cost to the government, and that low replacement rates were responsible for the long time to detection predicted by the model, but that improving the sensitivity of slaughterhouse screening and the probability that a slaughtered animal's herd of origin can be identified would result in faster detection times.

Minimization of bovine tuberculosis control costs in US dairy herds.

The objective of this study was to minimize the cost of controlling an isolated bovine tuberculosis (bTB) outbreak in a US dairy herd, using a stochastic simulation model of bTB with economic and biological layers. A model optimizer produced a control program that required 2-month testing intervals (TI) with 2 negative whole-herd tests to leave quarantine. This control program minimized both farm and government costs. In all cases, test-and-removal costs were lower than depopulation costs, although the variability in costs increased for farms with high holding costs or small herd sizes. Increasing herd size significantly increased costs for both the farm and the government, while increasing indemnity payments significantly decreased farm costs and increasing testing costs significantly increased government costs. Based on the results of this model, we recommend 2-month testing intervals for herds after an outbreak of bovine tuberculosis, with 2 negative whole herd tests being sufficient to lift quarantine. A prolonged test and cull program may cause a state to lose its bTB-free status during the testing period. When the cost of losing the bTB-free status is greater than $1.4 million then depopulation of farms could be preferred over a test and cull program.

The cost and benefit of Listeria monocytogenes food safety measures.

The objectives of this study were to evaluate economic techniques used to determine the cost and benefit of Listeria monocytogenes control and to estimate the economic optimum of L. monocytogenes food safety measures. The level of food safety measures is optimal if marginal benefit and marginal cost equate. Estimates of benefit and cost of L. monocytogenes food safety measures, from available published literature, are derived from different methods of economic analysis (willingness to pay, cost of illness, cost function, and event study methods). The estimated annual benefit and cost of L. monocytogenes food safety measures range from $2.3 billion to $22 billion and from $.01 billion to $2.4 billion, respectively. The estimated marginal benefit exceeds the estimated marginal cost, which implies that more food safety measures are warranted before the optimal level of L. monocytogenes food safety can be reached. However, due to considerable lack of data, the optimal level of L. monocytogenes food safety measures could not be estimated. When better data become available, this study can serve as a template for estimating the optimal level of food safety. The understanding of the economic optimum of food safety level will contribute to designing a control program that is economical and acceptable for US society.