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.

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.

Phenotypical resistance correlation networks for 10 non-typhoidal Salmonella subpopulations in an active antimicrobial surveillance programme.

Antimicrobials play a critical role in treating cases of invasive non-typhoidal salmonellosis (iNTS) and other diseases, but efficacy is hindered by resistant pathogens. Selection for phenotypical resistance may occur via several mechanisms. The current study aims to identify correlations that would allow indirect selection of increased resistance to ceftriaxone, ciprofloxacin and azithromycin to improve antimicrobial stewardship. These are medically important antibiotics for treating iNTS, but these resistances persist in non-Typhi Salmonella serotypes even though they are not licensed for use in US food animals. A set of 2875 Salmonella enterica isolates collected from animal sources by the National Antimicrobial Resistance Monitoring System were stratified in to 10 subpopulations based on serotype and host species. Collateral resistances in each subpopulation were estimated as network models of minimum inhibitory concentration partial correlations. Ceftriaxone sensitivity was correlated with other ß-lactam resistances, and less commonly resistances to tetracycline, trimethoprim-sulfamethoxazole or kanamycin. Azithromycin resistance was frequently correlated with chloramphenicol resistance. Indirect selection for ciprofloxacin resistance via collateral selection appears unlikely. Density of the ACSSuT subgraph resistance aligned well with the phenotypical frequency. The current study identifies several important resistances in iNTS serotypes and further research is needed to identify the causative genetic correlations.

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.

Use of an Individual-based Model to Control Transmission Pathways of Mycobacterium avium Subsp. paratuberculosis Infection in Cattle Herds.

Johne's disease (JD) is a chronic enteric disease in cattle caused by Mycobacterium avian subsp. paratuberculosis (MAP). Eradicating JD is a difficult task due to the long incubation period of MAP, inefficient diagnostic tests, and delayed clinical signs. Effective control strategies can help farmers to reduce prevalence, but those most acceptable to farmers combine specific information about lactation performance and testing results, which existing models do not provide. This paper presents an individual-based model of MAP infection dynamics and assesses the relative performance of the applied alternative control strategies. The base dairy herd model included the daily life events of a dairy cow and reflects several current dairy management processes. We then integrated MAP infection dynamics into the model. The model adopted four different test-based control strategies based on risk-based culling decisions and three hygiene scenarios. The model tracked the source of each infection and quantified the efficacy of each control strategy in reducing the risks of different transmission routes. The results suggest that risk-based culling can reduce prevalence compared with no control, but cannot eliminate the infection. Overall, this work provides not only a valuable tool to investigate MAP transmission dynamics but also offers adaptability to model similar infectious diseases.

The effect of Mycobacterium avium ssp. paratuberculosis infection on clinical mastitis occurrence in dairy cows.

Endemic diseases can be counted among the most serious sources of losses for livestock production. In dairy farms in particular, one of the most common diseases is Johne's disease, caused by Mycobacterium avium ssp. paratuberculosis (MAP). Infection with MAP causes direct costs because it affects milk production, but it has also been suspected to increase the risk of clinical mastitis (CM) among infected animals. This might contribute to further costs for farmers. We asked whether MAP infection represents a risk factor for CM and, in particular, whether CM occurrences were more common in MAP-infected animals. Our results, obtained by survival analysis, suggest that MAP-infected cows had an increased probability of experiencing CM during lactation. These results highlight the need to account for the interplay of infectious diseases and other health conditions in economic and epidemiological modeling. In this case, accounting for MAP-infected cows having an increased CM occurrence might have nonnegligible effects on the estimated benefit of MAP control.

Longitudinal relationship between fecal culture, fecal quantitative PCR, and milk ELISA in Mycobacterium avium ssp. paratuberculosis-infected cows from low-prevalence dairy herds.

Mycobacterium avium ssp. paratuberculosis (MAP), the causative agent of ruminant Johne's disease, presents a particular challenge with regard to infection mitigation on dairy farms. Diagnostic testing strategies to identify and quantify MAP and associated antibodies are imperfect, and certain facets of the relationship between diagnostic tests remain to be explored. Additional repeated-measures data from known infected animals are needed to complement the body of cross-sectional research on Johne's disease-testing methods. Statistical models that accurately account for multiple diagnostic results while adjusting for the effects of individual animals and herds over time can provide a more detailed understanding of the interplay between diagnostic outcomes. Further, test results may be considered as continuous wherever possible so as to avoid the information loss associated with dichotomization. To achieve a broader understanding of the relationship between diagnostic tests, we collected a large number of repeated fecal and milk samples from 14 infected cows, in addition to bulk milk samples, from 2 low-prevalence dairy herds in the northeast United States. Predominately through the use of mixed linear modeling, we identified strong associations between milk ELISA optical density, fecal quantitative PCR, and fecal culture in individual animals while concurrently adjusting for variables that could alter these relationships. Notably, we uncovered subtleties in the predictive abilities of fecal shedding level on milk ELISA results, with animals categorized as disease progressors reaching higher ELISA optical density levels. Moreover, we observed that spikes in fecal shedding could predict subsequent high ELISA values up to 2 mo later. We also investigated the presence of MAP in individual milk samples via PCR and noted an association between poor udder hygiene and MAP positivity in milk, suggesting some level of environmental contamination. The paucity of positive milk samples and the complete absence of detectable MAP in the bulk tank throughout the study period indicate that contamination of milk with MAP may not be of chief concern in low-prevalence herds. An enhanced understanding of the interrelationships between diagnostic tests can only benefit the development of testing strategies and objectives, which in turn may lessen MAP infection prevalence in dairy herds.

Models of antimicrobial pressure on intestinal bacteria of the treated host populations.

Antimicrobial drugs are used to treat pathogenic bacterial infections in animals and humans. The by-stander enteric bacteria of the treated host's intestine can become exposed to the drug or its metabolites reaching the intestine in antimicrobially active form. We consider which processes and variables need to be accounted for to project the antimicrobial concentrations in the host's intestine. Those include: the drug's fraction (inclusive of any active metabolites) excreted in bile; the drug's fractions and intestinal segments of excretion via other mechanisms; the rates and intestinal segments of the drug's absorption and re-absorption; the rates and intestinal segments of the drug's abiotic and biotic degradation in the intestine; the digesta passage time through the intestinal segments; the rates, mechanisms, and reversibility of the drug's sorption to the digesta and enteric microbiome; and the volume of luminal contents in the intestinal segments. For certain antimicrobials, the antimicrobial activity can further depend on the aeration and chemical conditions in the intestine. Model forms that incorporate the inter-individual variation in those relevant variables can support projections of the intestinal antimicrobial concentrations in populations of treated host, such as food animals. To illustrate the proposed modeling framework, we develop two examples of treatments of bovine respiratory disease in beef steers by oral chlortetracycline and injectable third-generation cephalosporin ceftiofur. The host's diet influences the digesta passage time, volume, and digesta and microbiome composition, and may influence the antimicrobial loss due to degradation and sorption in the intestine. We consider two diet compositions in the illustrative simulations. The examples highlight the extent of current ignorance and need for empirical data on the variables influencing the selective pressures imposed by antimicrobial treatments on the host's intestinal bacteria.

Economic consequences of paratuberculosis control in dairy cattle: A stochastic modeling study.

The cost of paratuberculosis to dairy herds, through decreased milk production, early culling, and poor reproductive performance, has been well-studied. The benefit of control programs, however, has been debated. A recent stochastic compartmental model for paratuberculosis transmission in US dairy herds was modified to predict herd net present value (NPV) over 25 years in herds of 100 and 1000 dairy cattle with endemic paratuberculosis at initial prevalence of 10% and 20%. Control programs were designed by combining 5 tests (none, fecal culture, ELISA, PCR, or calf testing), 3 test-related culling strategies (all test-positive, high-positive, or repeated positive), 2 test frequencies (annual and biannual), 3 hygiene levels (standard, moderate, or improved), and 2 cessation decisions (testing ceased after 5 negative whole-herd tests or testing continued). Stochastic dominance was determined for each herd scenario; no control program was fully dominant for maximizing herd NPV in any scenario. Use of the ELISA test was generally preferred in all scenarios, but no paratuberculosis control was highly preferred for the small herd with 10% initial prevalence and was frequently preferred in other herd scenarios. Based on their effect on paratuberculosis alone, hygiene improvements were not found to be as cost-effective as test-and-cull strategies in most circumstances. Global sensitivity analysis found that economic parameters, such as the price of milk, had more influence on NPV than control program-related parameters. We conclude that paratuberculosis control can be cost effective, and multiple control programs can be applied for equivalent economic results.

Comparative risk assessment for new cow-level Mycobacterium avium ssp. paratuberculosis infections between 3 dairy production types: Organic, conventional, and conventional-grazing systems.

Johne's disease, a granulomatous enteritis of ruminant animals, is a hidden threat on dairy farms, adversely affecting animal welfare as well as herd productivity. Control programs in the United States advocate for specific management practices to temper the spread of the causal organism (Mycobacterium avium ssp. paratuberculosis, MAP), such as improving calving area hygiene and limiting introduction of replacement stock with unknown infection status. A need remains for direct exploration of Johne's disease prevention strategies in the United States with respect to production type. Alongside the growing demand for organic products, the safety of organic dairy practices with respect to MAP control is warranted. Further, conventional herds for which organic practices such as pasture grazing are used should be situated within the risk spectrum. We developed a risk assessment model using the US Voluntary Bovine Johne's Disease Control Program as a framework, with the goal of evaluating the risk of new cow-level MAP infections. A total of 292 organic and conventional farms in 3 states were surveyed on management practices, and an overall analysis was conducted in which each farm was first scored on individual practices using a range of "no risk" to "high risk," according to the literature. The sum of all risk factors was then analyzed to quantify and compare the risk burden for each production type. Organic herds received higher overall risk scores compared with both conventional grazing and nongrazing subtypes. To identify which factors contributed to the overall increased risk for organic herds, the management practices were categorized and evaluated by logistic regression. We determined that the increased risk incurred by organic herds was predominantly due to decisions made in the calving area and preweaned calf group. However, although certain individual risk factors related to calf management are commonly involved in prevention strategies (e.g., cow/calf separation) and were thus included in the overall risk assessment, empirical evidence linking them to the spread of MAP is lacking. Instead, these factors are problematic when executed with other management decisions, leading to a hypothesized synergism of transmission risk. To this end, we developed a set of compound risk factors, which were also evaluated as outcomes in logistic regression models, with production type serving as the predictor of interest. Organic farms in our study were more susceptible to risks associated with the synergism of study variables. Notably, organic producers were most likely to allow calves to spend extended time with the dam, while also lacking a dedicated calving area. Additionally, calves in organic herds were more often permitted to nurse even with poor udder hygiene on farm. A heightened vigilance toward calving area hygiene is therefore indicated for these herds.

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

This study used an existing dynamic optimization model to compare costs of common treatment protocols and J5 vaccination for clinical mastitis in US dairy herds. Clinical mastitis is an infection of the mammary gland causing major economic losses in dairy herds due to reduced milk production, reduced conception, and increased risk of mortality and culling for infected cows. Treatment protocols were developed to reflect common practices in dairy herds. These included targeted therapy following pathogen identification, and therapy without pathogen identification using a broad-spectrum antimicrobial or treating with the cheapest treatment option. The cost-benefit of J5 vaccination was also estimated. Effects of treatment were accounted for as changes in treatment costs, milk loss due to mastitis, milk discarded due to treatment, and mortality. Following ineffective treatments, secondary decisions included extending the current treatment, alternative treatment, discontinuing treatment, and pathogen identification followed by recommended treatment. Average net returns for treatment protocols and vaccination were generated using an existing dynamic programming model. This model incorporates cow and pathogen characteristics to optimize management decisions to treat, inseminate, or cull cows. Of the treatment protocols where 100% of cows received recommended treatment, pathogen-specific identification followed by recommended therapy yielded the highest average net returns per cow per year. Out of all treatment scenarios, the highest net returns were achieved with selecting the cheapest treatment option and discontinuing treatment, or alternate treatment with a similar spectrum therapy; however, this may not account for the full consequences of giving nonrecommended therapies to cows with clinical mastitis. Vaccination increased average net returns in all scenarios.

Implications of PCR and ELISA results on the routes of bulk-tank contamination with Mycobacterium avium ssp. paratuberculosis.

Mycobacterium avium ssp. paratuberculosis (MAP), the etiologic agent of Johne's disease in dairy cattle, may enter the bulk tank via environmental contamination or direct excretion into milk. Traditionally, diagnostics to identify MAP in milk target either MAP antibodies (by ELISA) or the organism itself (by culture or PCR). High ELISA titers may be directly associated with excretion of MAP into milk but only indirectly linked to environmental contamination of the bulk tank. Patterns of bulk-milk ELISA and bulk-milk PCR results could therefore provide insight into the routes of contamination and level of infection or environmental burden. Coupled with questionnaire responses pertaining to management, the results of these diagnostic tests could reveal correlations with herd characteristics or on-farm practices that distinguish herds with high and low environmental bulk-tank MAP contamination. A questionnaire on hygiene, management, and Johne's specific parameters was administered to 292 dairy farms in New York, Oregon, and Wisconsin. Bulk-tank samples were collected from each farm for evaluation by real-time PCR and ELISA. Before DNA extraction and testing of the unknown samples, bulk-milk template preparation was optimized with respect to parameters such as MAP fractionation patterns and lysis. Two regression models were developed to explore the relationships among bulk-tank PCR, ELISA, environmental predictors, and herd characteristics. First, ELISA optical density (OD) was designated as the outcome in a linear regression model. Second, the log odds of being PCR positive in the bulk tank were modeled using binary logistic regression with penalized maximum likelihood. The proportion of PCR-positive bulk tanks was highest for New York and for organic farms, providing a clue as to the geographical patterns of MAP-positive bulk-tank samples and relationship to production type. Bulk-milk PCR positivity was also higher for large relative to small herds. The models revealed that bulk-milk PCR result could predict ELISA OD, with PCR-positive results corresponding to high bulk-milk ELISA titers. Similarly, ELISA was a predictor of PCR result, although the association was stronger for organic farms. Despite agreement between high bulk-milk ELISA titers and positive PCR results, a large proportion of high ELISA farms had PCR-negative bulk tanks, suggesting that farms are able to maintain satisfactory hygiene and management despite a presence of MAP in these herds.

The effects of progressing and nonprogressing Mycobacterium avium ssp. paratuberculosis infection on milk production in dairy cows.

Longitudinal data from 3 commercial dairy herds in the northeast United States, collected from 2004 to 2011, were analyzed to determine the effect of Mycobacterium avium ssp. paratuberculosis (MAP) infection status and progression path on milk production. Disease status, as indicated by MAP test results, was determined through quarterly ELISA serum testing, biannual fecal culture, and culture of tissues and feces at slaughter. Milk production data were collected from the Dairy Herd Information Association. Animals with positive MAP test results were categorized, based on test results over the full course of the study, as high path (at least one high-positive culture) or low path (at least one positive culture or ELISA). The cumulative numbers of positive ELISA and culture results were recorded. The effects of both MAP infection path, status, and number of positive tests on milk production were analyzed using a mixed linear model with an autocorrelation random effect structure. Low- and high-path animals produced more milk before their first positive test than always-negative animals, especially high-path animals. Although mean production decreased after a first positive test, low-path animals were shown to recover some productivity. High-path animals continued to exhibit a decrease in milk production, especially after their first high-positive fecal culture. These results show that not all animals that test positive for MAP will have long-term production losses. Milk production decreased significantly with each additional positive test. Ultimately, production loss appeared to be a function of MAP infection progression.

Effect of on-farm use of antimicrobial drugs on resistance in fecal Escherichia coli of preweaned dairy calves.

Respiratory disease and diarrhea are the 2 most common diseases that result in the use of antimicrobial drugs in preweaned calves. Because the use of drugs in food animals, including dairy calves, has the potential for generating cross-resistance to drugs used in human medicine, it is vital to propose farm practices that foster the judicious use of antimicrobials while assuring animal health and productivity. The objective of this study was to use dairy farm calf treatment records to identify antimicrobial drug treatments in calves and to evaluate their effects on the prevalence of antimicrobial-resistant Escherichia coli from rectal swabs of preweaned dairy calves. Eight farms from central New York participated in the study, 3 farms using individual pen housing management and 5 farms using group pen housing management. Eligible study farms could not add antimicrobial drugs to the milk fed to preweaned calves and were required to have farm records documenting antimicrobial drug treatment of calves from birth to weaning. Three fecal E. coli isolates per calf were tested for susceptibility to 12 antimicrobial drugs using a Kirby-Bauer disk diffusion assay. A total of 473 calves were sampled, from which 1,423 commensal E. coli isolates were tested. Of the 9 antimicrobial drugs used on study farms, only enrofloxacin was significantly associated with reduced antimicrobial susceptibility of E. coli isolates, although treatment with ceftiofur was associated with reduced susceptibility to ceftriaxone. The median numbers of days from treatment with ceftiofur and enrofloxacin to rectal swab sampling of calves were 16 d (range: 1-39) and 12 d (range: 6-44), respectively. At the isolate level, treatment with enrofloxacin resulted in odds ratios of 2 [95% confidence interval (CI): 1-4] and 3 (95% CI: 2-6), respectively, for isolation of nonsusceptible E. coli to nalidixic acid and ciprofloxacin compared with calves not treated with enrofloxacin. Treatment with ceftiofur resulted in an odds ratio of 3 (95% CI: 0.9-12) for isolation of nonsusceptible E. coli to ceftriaxone compared with calves not treated with ceftiofur. Treatment with enrofloxacin resulted in selection of isolates that presented phenotypic resistance to both ciprofloxacin and ceftriaxone. Treatment with ceftiofur resulted in a higher prevalence of isolates resistant to ≥3 antimicrobial drugs (97%) compared with no treatment with ceftiofur (73%). These findings reinforce the necessity for continued implementation of practices at the dairy farm that support the sustainable and judicious use of antimicrobial drugs in dairy calves.

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.

Antimicrobial drug resistance patterns among cattle- and human-associated Salmonella strains.

During the year 2004, 178 human and 158 bovine clinical Salmonella isolates were collected across New York State to better understand the transmission dynamics and genetic determinants of antimicrobial resistance among human and bovine hosts. Serotyping, sequence typing, and pulsed-field gel electrophoresis typing results have been reported previously. Here we tested all isolates for phenotypic susceptibility to 15 antimicrobial drugs that are part of the National Antimicrobial Monitoring System bovine susceptibility panel. PCR was performed on a representative subset of unique isolates (n = 53) to screen for the presence of 21 known antimicrobial resistance genes (i.e., ampC, blaTEM-1, blaCMY-2, blaPSE-1, cat1, cat2, cmlA, flo, aadA1, aadA2, aacC2, strA, strB, aphA1-IAB, dhrfI, dhrfXII, sulI, sulII, tetA, tetB, and tetG); selected fluoroquinolone- and nalidixic acid-resistant (n = 3) and -sensitive (n = 6) isolates were also tested for known resistance-conferring mutations in gyrA and parC. Genes responsible for antimicrobial resistance were shared among isolates of human and bovine origin. However, bovine isolates were significantly more likely than human isolates to be multidrug resistant (P < 0.0001; Fisher's exact test). Our analyses showed perfect categorical agreement between phenotypic and genotypic resistance for beta-lactam and chloramphenicol. Our data confirm that resistance profiles of amoxicillin-clavulanic acid, chloramphenicol, kanamycin, and tetracycline were strongly associated with the presence of blaCMY or ampC, flo, aphA1-IAB, and tetA, respectively. Our findings provide evidence for the clinical value of genotypic resistance typing if incorporating multiple known genes that can confer a phenotypic resistance profile.