Prevalence and associations between bacterial isolates from dry mammary glands of dairy cows

To assess the prevalence and patterns of bacterial isolates, cultures were made from the dry mammary glands of dairy cows in six commercial dairy herds in the UK. Milk samples were taken from all four quarters of 480 cows at drying off and at weekly intervals from 14 days before to seven days after calving. A major mastitis pathogen was isolated from at least one quarter of 220 (45.8 per cent) of the cows and from more than one quarter of 90 (18.8 per cent) of them. During the late dry to calving period, of the 957 quarters with three culture results, a major mastitis pathogen was cultured from 236 (24.7 per cent) quarters of 186 (38.8 [corrected] per cent) cows. The most commonly isolated major pathogen was Escherichia coli, followed by Streptococcus uberis and coagulase-positive staphylococci. There were significant differences between the patterns of isolates from different farms and in different calving months, suggesting that the rate of infection was partially dependent on external conditions. The isolation of E. coli, S. uberis or coagulase-positive staphylococci from a cow during the late dry/periparturient period was associated with an increased risk of that cow being culled in the next lactation. Bayesian general linear mixed models were used to assess the associations between the different bacterial species. The probability of isolating either E. coli or S. uberis was significantly greater when the other organism was cultured in a milk sample; this was also true of coagulase-positive staphylococci and S. uberis. When Corynebacterium species were isolated from a milk sample, the probability of isolating coagulase-positive staphylococci or S. uberis decreased significantly, and when coagulase-negative staphylococci were isolated the probability of isolating coagulase-positive staphylococci was reduced.

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

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

Associations between somatic cell count patterns and the incidence of clinical mastitis

Associations between clinical mastitis (CM) and the proportional distribution of patterns in somatic cell count (SCC) on a herd level were determined in this study. Data on CM and SCC over a 12-month period from 274 Dutch herds were used. The dataset contained parts of 29,719 lactations from 22,955 cows of different parities. In total, 207,079 SCC test-days were recorded with 5719 cases of CM; 1561 cases were associated with environmental pathogens (ENV_CM), and 2681 with contagious pathogens (CONT_CM). Definitions of patterns in SCC were based on 3, 4, or 5 consecutive test-day recordings of SCC that differentiated between short or longer periods of increased SCC, and also between lactations with and without recovery. The distribution of those patterns (relative to their maximum) varied among herds. The distribution of SCC patterns was correlated with the incidence rate of CM. Herds with a relatively frequent quick recovery pattern had a 2.5 times more chance of being classified in the upper quartile for CM. These herds also had 2.1 times more chance of being classified in the upper quartile for ENV_CM but only 0.4 times for CONT_CM. Herds with a relatively frequent no recovery pattern had less chance (odds ratio=0.5) of being classified in the lower quartile for CONT_CM. Since the distributions of SCC patterns were indicative for overall, environmental and contagious CM, the necessity to introduce pathogen-specific mastitis control programs in a herd could be determined based on the mean incidences of SCC patterns in that herd.

Salmonella Dublin infection in dairy cattle: risk factors for becoming a carrier

Long-term Salmonella Dublin carrier animals harbor the pathogen in lymph nodes and internal organs and can periodically shed bacteria through feces or milk, and contribute to transmission of the pathogen within infected herds. Thus, it is of great interest to reduce the number of new carrier animals in cattle herds. An observational field study was performed to evaluate factors affecting the risk that dairy cattle become carrier animals after infection with Salmonella Dublin. Based on repeated sampling, cattle in 12 Danish dairy herds were categorized according to course of infection, as either carriers (n = 157) or transiently infected (n = 87). The infection date for each animal was estimated from fecal excretion and antibody responses. The relationship between the course of infection (carrier versus transiently infected) and risk factors were analyzed using a random effect multilevel, multivariable logistic regression model. The animals with the highest risk of becoming carriers were heifers infected between the age of 1 year and 1st calving, and cows infected around the time of calving. The risk was higher in the first two quarters of the year (late Winter to Spring), and when the prevalence of potential shedders in the herd was low. The risk also varied between herds. The herds with the highest risk of carrier development were herds with clinical disease outbreaks during the study period. These findings are useful for future control strategies against Salmonella Dublin, because they show the importance of optimized calving management and management of heifers, and because they show that even when the herd prevalence is low, carriers are still being produced. The results raise new questions about the development of the carrier state in cattle after infection with low doses of Salmonella Dublin.

Mastitis-causing streptococci are important contributors to bacterial counts in raw bulk tank milk

The objective of this study was to probe the contribution of streptococci to the microbial quality of raw milk. Over a 5-month period, bulk tank milk samples from 48 New York State dairy farms were analyzed qualitatively for bacterial ecology and quantitatively for total bacterial, streptococcal, staphylococcal, and gram-negative bacterial counts. Linear regression analysis was used to determine the contribution of differential counts to total bacterial counts. Streptococci, staphylococci, and gram-negative bacteria accounted for 69, 3, and 3% of total bacterial count variability, respectively. Randomly selected Streptococcus isolates from each bulk tank milk sample were identified to species by means of the API 20 STREP identification system. The most commonly identified streptococcal species were Streptococcus uberis, Aerococcus viridans, and Streptococcus agalactiae, which were detected in 81, 50, and 31% of 48 bulk tank samples, respectively. For five herds, S. uberis isolates from bulk tank milk and individual cows were characterized by PvuII ribotyping. A farm-specific dominant ribotype was found in each bulk tank sample, and that ribotype was isolated from at least one cow within each herd of origin. Bacteriological and strain typing data indicate that control of streptococci, specifically mastitis-causing species, is important for improvement of the microbial quality of raw milk in New York State.

TRANSITION MODELS TO ASSESS RISK FACTORS FOR NEW AND PERSISTENT TRYPANOSOME INFECTIONS IN CATTLE—ANALYSIS OF LONGITUDINAL DATA FROM THE GHIBE VALLEY, SOUTHWEST ETHIOPIA

The objective of this study was to apply transition models to distinguish between factors associated with both incident and persistent trypanosome infections. Data collected from 1561 cattle were analyzed from a long-term study involving 8 herds in which both trypanosome infections (a total of 56,931 cattle sampling-months) and tsetse (Glossina spp.) challenge were monitored monthly from March 1986 to March 1998. Both pour-on and insecticide-target tsetse control programs and mass treatment with diminazene aceturate before tsetse control were associated with significant decreases in both incidence and persistence of trypanosome infection relative to noncontrol periods, as were seasonal and sex effects. The magnitudes of the effects were, however, often different for new and persistent infections. For persistence of infection, there were 2 trends. In general, the duration of infection increased during the study, despite the regular treatment with diminazene aceturate. The transition model had 2 major benefits. The first was to identify an increasing duration of infections with time, taking into account other factors associated with increasing infection risk. The second was to highlight different patterns in the effects of certain factors on new and persistent trypanosome infections.

The use of Markov chain Monte Carlo for analysis of correlated binary data: patterns of somatic cells in milk and the risk of clinical mastitis in dairy cows

Two analytical approaches were used to investigate the relationship between somatic cell concentrations in monthly quarter milk samples and subsequent, naturally occurring clinical mastitis in three dairy herds. Firstly, cows with clinical mastitis were selected and a conventional matched analysis was used to compare affected and unaffected quarters of the same cow. The second analysis included all cows, and in order to overcome potential bias associated with the correlation structure, a hierarchical Bayesian generalised linear mixed model was specified. A Markov chain Monte Carlo (MCMC) approach, that is Gibbs sampling, was used to estimate parameters. The results of both the matched analysis and the hierarchical modelling suggested that quarters with a somatic cell count (SCC) in the range 41,000-100,000 cells/ml had a lower risk of clinical mastitis during the next month than quarters <41,000 cell/ml. Quarters with an SCC >200,000 cells/ml were at the greatest risk of clinical mastitis in the next month. There was a reduced risk of clinical mastitis between 1 and 2 months later in quarters with an SCC of 81,000-150,000 cells/ml compared with quarters below this level. The hierarchical modelling analysis identified a further reduced risk of clinical mastitis between 2 and 3 months later in quarters with an SCC 61,000-150,000 cells/ml, compared to other quarters. We conclude that low concentrations of somatic cells in milk are associated with increased risk of clinical mastitis, and that high concentrations are indicative of pre-existing immunological mobilisation against infection. The variation in risk between quarters of affected cows suggests that local quarter immunological events, rather than solely whole cow factors, have an important influence on the risk of clinical mastitis. MCMC proved a useful tool for estimating parameters in a hierarchical Bernoulli model. Model construction and an approach to assessing goodness of model fit are described.

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

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

Somatic cell count distributions during lactation predict clinical mastitis

This research investigated somatic cell count (SCC) records during lactation, with the purpose of identifying distribution characteristics (mean and measures of variation) that were most closely associated with clinical mastitis. Three separate data sets were used, one containing quarter SCC (n = 1444) and two containing cow SCC (n = 933 and 11,825). Clinical mastitis was defined as a binary outcome, present or absent, for each lactation, and SCC were log (base 10) transformed. A generalized linear mixed model within a Bayesian framework was used for analysis. Parameters were estimated using Markov Chain Monte Carlo with Gibbs sampling. Results from the 3 data sets were similar. Increased maximum and standard deviation log SCC during lactation, rather than increased geometric mean, were the best overall indicators of clinical mastitis. Distributions of SCC were also investigated separately for different mastitis pathogens. Increased maximum log SCC was associated with clinical mastitis caused by all pathogen types. Increased standard deviation log SCC was associated with Staphylococcus aureus, and Streptococcus uberis clinical mastitis and increased coefficient of variation log SCC (standard deviation divided by mean) was associated with Escherichia coli clinical mastitis. Increased geometric mean lactation SCC was associated with an increased risk of Staph. aureus clinical mastitis but a reduced risk of E. coli clinical mastitis. Our results suggest that using measures of variation and maximum cow SCC would enhance the accuracy of predicting clinical mastitis, compared with geometric mean SCC, and therefore improve genetic programs that aim to select for clinical mastitis resistance. The results are also consistent with low SCC increasing susceptibility to some mastitis pathogens.

Ecology and transmission of Listeria monocytogenes infecting ruminants and in the farm environment

A case-control study involving 24 case farms with at least one recent case of listeriosis and 28 matched control farms with no listeriosis cases was conducted to probe the transmission and ecology of Listeria monocytogenes on farms. A total of 528 fecal, 516 feed, and 1,012 environmental soil and water samples were cultured for L. monocytogenes. While the overall prevalence of L. monocytogenes in cattle case farms (24.4%) was similar to that in control farms (20.2%), small-ruminant (goat and sheep) farms showed a significantly (P < 0.0001) higher prevalence in case farms (32.9%) than in control farms (5.9%). EcoRI ribotyping of clinical (n = 17) and farm (n = 414) isolates differentiated 51 ribotypes. L. monocytogenes ribotypes isolated from clinical cases and fecal samples were more frequent in environmental than in feed samples, indicating that infected animals may contribute to L. monocytogenes dispersal into the farm environment. Ribotype DUP-1038B was significantly (P < 0.05) associated with fecal samples compared with farm environment and animal feedstuff samples. Ribotype DUP-1045A was significantly (P < 0.05) associated with soil compared to feces and with control farms compared to case farms. Our data indicate that (i) the epidemiology and transmission of L. monocytogenes differ between small-ruminant and cattle farms; (ii) cattle contribute to amplification and dispersal of L. monocytogenes into the farm environment, (iii) the bovine farm ecosystem maintains a high prevalence of L. monocytogenes, including subtypes linked to human listeriosis cases and outbreaks, and (iv) L. monocytogenes subtypes may differ in their abilities to infect animals and to survive in farm environments.

Association of cow and quarter-level factors at drying-off with new intramammary infections during the dry period

Our objective was to describe cow and quarter-level factors associated with drying-off, and to evaluate their impacts on new intramammary infections (IMI) during the dry period. Data from 300 cows in five research herds were collected starting 2 weeks prior to scheduled drying-off. Variables of interest included daily milk production, teat-end integrity, formation of the teat-canal keratin plug, and quarter-milk bacteriological culture results. Overall, 11% of quarters developed new IMI in the dry period; this varied by herd, parity and time of the study. Most new IMI were caused by environmental streptococci and coliform organisms (34 and 30%, respectively). Quarters that had a cracked teat-end had higher odds of developing new infections than those without cracks (15 and 10%, respectively). Quarters that formed a keratin plug early in the dry period had a lower odds than those that did not close (10 and 14%, respectively). After 6 dry weeks, 23% of quarters were still open. The hazard of quarters closing if milk production on the day prior to drying-off was >21 kg 1.8-times less.

Associations Between Pathogen-Specific Cases of Clinical Mastitis and Somatic Cell Count Patterns

Associations were estimated between pathogen-specific cases of clinical mastitis (CM) and somatic cell count (SCC) patterns based on deviations from the typical curve for SCC during lactation and compared with associations between pathogen-specific CM and lactation average SCC. Data from 274 Dutch herds recording CM over an 18-mo period were used. Pathogens found were Staphylococcus aureus, coagulase-negative staphylococci, Escherichia coli, Streptococcus dysgalactiae, Streptococcus uberis, streptococci other than Strep. dysgalactiae and Strep. uberis, and culture-negative samples. The dataset contained 245,595 test-day records on SCC, recorded in 24,012 lactations of 19,733 cows of different parities. Pattern definitions were based on three or five consecutive test-day records. The patterns differentiated between a short or longer period of increased SCC and also between lactations with and without recovery. Logistic regression was applied to identify associations between presence of patterns and occurrence of pathogens. Occurrence of overall CM in a lactation is equally or even more accurately predicted by the presence of SCC in that lactation, than by a lactation average SCC of more than 200,000 cells/mL. Patterns can also distinguish between chances of risk for specific mastitis-causing pathogens. Clinical E. coli mastitis was significantly associated with the presence of a short peak in SCC, whereas Staph. aureus was associated with long increased SCC. Streptococcus dysgalactiae was not strongly associated with any of the defined patterns of peaks in SCC, and no single unambiguous pattern was found for Strep. uberis.

Prevalence estimates for paratuberculosis adjusted for test variability using Bayesian analysis

The ELISA tests that are available to detect an infection with Mycobacterium avium subsp. paratuberculosis (MAP) have a limited validity expressed as the sensitivity (Se) and specificity (Sp). In many studies, the Se and Sp of the tests are treated as constants and this will result in an underestimation of the variability of the true prevalence (TP). Bayesian inference provided a natural framework for using information on the test variability (i.e., the uncertainty) in the estimates of test Se and Sp when estimating the TP. Data from two prevalence studies for MAP using an ELISA in several regions in two locations were available for the analyses. In location 1, all cattle of at least 3 years of age were sampled in approximately 90 randomly sampled herds in each of the four regions of the country. In location 2, in 30 randomly sampled herds in each of three regions, approximately 30 randomly selected cows were sampled. Information about the unknown test Se and Sp and MAP prevalence was incorporated into a Bayesian model by joint prior probability distributions. Posterior estimates were obtained by combining the actual likelihood with the prior distributions using Bayes' formula. The corrected cow-level TP (proportion of infected cows in a herd) was low, 5.8 and 3.6% in locations 1 and 2, respectively. Certain regions within a location differed significantly in herd-level TP (proportion of infected herds). The herd-level TP was 54.3% in location 1 (95% credible interval (CI) 46.1, 63.3%) and 32.9% in location 2 (95% CI: 14.4, 73.3%). The variation in the herd-level TP estimate for location 2 was more than three times as large as the variation in location 1 mainly because of the relatively small number of investigated herds in location 2. In future prevalence studies for MAP, sample size calculations should be based on a very low cow-level prevalence. Approximately 50 and 90% of the herds in the current study had an estimated cow-level TP below 4 and 10%, respectively.

Analysis of correlated discrete observations: background, examples and solutions

The goal of this paper is to highlight the use and interpretation of statistical techniques that account for correlation in epidemiological data. A conceptual statistical background is provided, and the main types of regression models for correlated data are highlighted. These models include marginal models, random effect models and transitional regression models. For each model type an example with data from the veterinary literature is provided. The examples are specifically used to highlight estimation procedures for parameters, and the interpretation of the estimated parameters. This paper emphasizes that statistical techniques and software to fit them are more widely available now, but that parameters have different interpretations in different model types. Consequently, we stress the importance of focusing on choosing the most appropriate model for the specific purpose of the analysis.

Transmission of bovine herpesvirus 1 within and between herds on an island with a BHV1 control programme

Transmission of bovine herpesvirus 1 (BHV1) within and between herds was studied on the island of Ameland, The Netherlands. There were 50 herds with 3300 head of cattle on the island. Herds were divided into three groups: (1) only containing seronegative cattle, (2) containing seronegative cattle and vaccinated seropositive cattle, and (3) containing only vaccinated cattle. All 23 herds in groups 1 and 2 were monitored. Three major outbreaks of BHV1 infections were observed due to the introduction of infectious cattle. Another major outbreak was most likely induced by reactivation of latent BHV1 in seropositive cattle. The basic reproduction ratio within these herds was estimated at least 4. Only one of these outbreaks led to three secondary outbreaks in susceptible herds in which all cattle were seronegative. These outbreaks were most likely due to respectively, direct animal contact, human transmission, and aerogenic transmission. The basic reproduction ratio between herds in this study was estimated to be 0.6.

Pooled fecal culture sampling for Mycobacterium avium subsp. paratuberculosis at different herd sizes and prevalence

A stochastic spreadsheet model was developed to obtain estimates of the costs of whole herd testing on dairy farms for Mycobacterium avium subsp. paratuberculosis (Map) with pooled fecal samples. The optimal pool size was investigated for 2 scenarios, prevalence (a low-prevalence herd [< or = 5%] and a high-prevalence herd [> 5%]) and for different herd sizes (100-, 250-, 500- and 1,000-cow herds). All adult animals in the herd were sampled, and the samples of the individuals were divided into equal sized pools. When a pool tested positive, the manure samples of the animals in the pool were tested individually. The individual samples from a negative pool were assumed negative and not tested individually. Distributions were used to model the uncertainty about the sensitivity of the fecal culture at farm level and Map prevalence. The model randomly allocated a disease status to the cows (not shedding, low Map shedder, moderate Map shedder, and heavy Map shedder) on the basis of the expected prevalence in the herd. Pooling was not efficient in 100-cow and 250-cow herds with low prevalence because the probability to detect a map infection in these herds became poor (53% and 88%) when samples were pooled. When samples were pooled in larger herds, the probability to detect at least 1 (moderate to heavy) shedder was > 90%. The cost reduction as a result of pooling varied from 43% in a 100-cow herd with a high prevalence to 71% in a 1,000-cow herd with a low prevalence. The optimal pool size increased with increasing herd size and varied from 3 for a 500-cow herd with a low prevalence to 5 for a 1,000-cow herd with a high prevalence.

Clinical, epidemiological and molecular characteristics of Streptococcus uberis infections in dairy herds

A longitudinal observational study (18 months) was carried out in two Dutch dairy herds to explore clinical, epidemiological and molecular characteristics of Streptococcus uberis mastitis. Infections (n = 84) were detected in 70 quarters of 46 cows. Bacterial isolates were characterized at strain level by random amplified polymorphic DNA (RAPD) fingerprinting. Persistent infections were usually attributable to one strain, while recurrent infections could be caused by different strains. When multiple quarters of a cow were infected, infections were mostly caused by one strain. In each herd, multiple strains were identified yet one strain predominated. The majority of all infections were subclinical, and infections attributed to predominant strains were more chronic than infections attributed to other strains. Epidemiological and molecular data suggest infection from environmental sources with a variety of S. uberis strains as well as within-cow and between-cow transmission of a limited number of S. uberis strains, with possible transfer of bacteria via the milking machine.

Efficacy of intramammary tilmicosin and risk factors for cure of Staphylococcus aureus infection in the dry period

The objective ofthis study was to evaluate the efficacy of intramammary tilmicosin, administered at drying-off, for eliminating Staphylococcus aureus infection, and to identify risk factors for S. aureus cure during the dry period. A total of 219 naturally infected cows, representing 308 quarters, were randomized to receive either one of two treatments at drying-off. Cows received either an intramammary infusion of 500 mg of benzathine cloxacillin, or a sterile solution containing 1,500 mg of tilmicosin. All cows had quarter milk samples taken aseptically three times before dry-off, and at wk 1, 2, and 4 of the subsequent lactation. Overall, 62% of cows and 67.5% of quarters infected with S. aureus cured during the dry period. The cure following administraton of tilmicosin was 67.3 and 72.5% for cows and quarters, respectively. By comparison, the cure achieved with cloxacillin was 56.9 and 62.9% of cows and quarters. Cows receiving tilmicosin were 2.1 times more likely to cure. The cure rate for cows decreased as the linear score on the last DHI test increased, and as the amount of S. aureus being shed increased. Quarters that cultured positive multiple times before drying-off were less likely to cure. Staphylococcus aureus infections located in front quarters of the udder were 2 times more likely to cure than those in hind quarters. Results of this study demonstrate that intramammary tilmicosin at drying-off is efficacious in curing existing S. aureus during the dry period. Risk factors associated with the cure of S. aureus were identified.

The efficacy of intramammary tilmicosin at drying-off, and other risk factors for the prevention of new intramammary infections during the dry period

The objective of this study was to compare the efficacy of an intramammary infusion, containing tilmicosin phosphate, to an infusion of a negative control intramammary placebo for preventing new intramammary infections (IMI) during the dry period. Cows were enrolled from 24 dairy herds from three geographical regions of Canada. Data from 248 cows and 938 bacteriologically negative quarters at drying-off are summarized. Overall, the rate of new IMI during the dry period was 16.7% of quarters. The new infection rates for quarters that received intramammary tilmicosin compared with the intramammary placebo were 14.4 and 19.4%, respectively. The majority of new IMI was caused by coagulase-negative staphylococci (49%) and environmental streptococcal organisms (26.8%). The probability for quarters to develop new IMI in the dry period was significantly increased when cows had higher milk production before drying-off (P = 0.04), when cows had longer dry periods (P = 0.02), and when dry cows were housed in tie-stall barns (P = 0.002). Higher parity cows and those that had a linear score somatic cell count (SCC) above 4 on the last DHI test were also at increased risk for new IMI (P < 0.10). Administration of intramammary tilmicosin appears to be an efficacious therapy for prevention of new IMI; however, there is currently no approved intramammary formulation of this product available. Use of blanket dry cow antibiotic therapy compared to selective dry cow therapy, as well as the importance of identifying risk factors and managing the environment of dry cows are discussed.

Comparison of Staphylococcus aureus isolates from bovine and human skin, milking equipment, and bovine milk by phage typing, pulsed-field gel electrophoresis, and binary typing

Staphylococcus aureus isolates (n = 225) from bovine teat skin, human skin, milking equipment, and bovine milk were fingerprinted by pulsed-field gel electrophoresis (PFGE). Strains were compared to assess the role of skin and milking equipment as sources of S. aureus mastitis. PFGE of SmaI-digested genomic DNA identified 24 main types and 17 subtypes among isolates from 43 herds and discriminated between isolates from bovine teat skin and milk. Earlier, phage typing (L. K. Fox, M. Gershmann, D. D. Hancock, and C. T. Hutton, Cornell Vet. 81:183-193, 1991) had failed to discriminate between isolates from skin and milk. Skin isolates from humans belonged to the same pulsotypes as skin isolates from cows. Milking equipment harbored strains from skin as well as strains from milk. We conclude that S. aureus strains from skin and from milk can both be transmitted via the milking machine, but that skin strains are not an important source of intramammary S. aureus infections in dairy cows. A subset of 142 isolates was characterized by binary typing with DNA probes developed for typing of human S. aureus. Typeability and overall concordance with epidemiological data were lower for binary typing than for PFGE while discriminatory powers were similar. Within several PFGE types, binary typing discriminated between main types and subtypes and between isolates from different herds or sources. Thus, binary typing is not suitable as replacement for PFGE but may be useful in combination with PFGE to refine strain differentiation.

The structural identifiability and parameter estimation of a multispecies model for the transmission of mastitis in dairy cows with postmilking teat disinfection

A mathematical model for the transmission of two interacting classes of mastitis causing bacterial pathogens in a herd of dairy cows is presented and applied to a specific data set. The data were derived from a field trial of a specific measure used in the control of these pathogens, where half the individuals were subjected to the control and in the others the treatment was discontinued. The resultant mathematical model (eight non-linear simultaneous ordinary differential equations) therefore incorporates heterogeneity in the host as well as the infectious agent and consequently the effects of control are intrinsic in the model structure. A structural identifiability analysis of the model is presented demonstrating that the scope of the novel method used allows application to high order non-linear systems. The results of a simultaneous estimation of six unknown system parameters are presented. Previous work has only estimated a subset of these either simultaneously or individually. Therefore not only are new estimates provided for the parameters relating to the transmission and control of the classes of pathogens under study, but also information about the relationships between them. We exploit the close link between mathematical modelling, structural identifiability analysis, and parameter estimation to obtain biological insights into the system modelled.

A mathematical model of Staphylococcus aureus control in dairy herds

An ordinary differential equation model was developed to simulate dynamics of Staphylococcus aureus mastitis. Data to estimate model parameters were obtained from an 18-month observational study in three commercial dairy herds. A deterministic simulation model was constructed to estimate values of the basic (R0) and effective (Rt) reproductive number in each herd, and to examine the effect of management on mastitis control. In all herds R0 was below the threshold value 1, indicating control of contagious transmission. Rt was higher than R0 because recovered individuals were more susceptible to infection than individuals without prior infection history. Disease dynamics in two herds were well described by the model. Treatment of subclinical mastitis and prevention of influx of infected individuals contributed to decrease of S. aureus prevalence. For one herd, the model failed to mimic field observations. Explanations for the discrepancy are given in a discussion of current knowledge and model assumptions.

Influence of dry period bacterial intramammary infection on clinical mastitis in dairy cows

Milk samples were taken from 1920 quarters (480 cows, six herds) on four occasions to examine the relationship between quarter level intramammary infection (IMI) during the dry period and clinical mastitis in the next lactation. All quarters were sampled at drying off and within 1 wk of calving, and two quarters from each cow were sampled both 0 to 7 and 8 to 14 d before calving. Milk samples were collected from all cases of clinical mastitis during the following lactation. Logistic regression models were developed to investigate the associations between IMI present during the sampling period and clinical mastitis. The probability of a quarter succumbing to clinical mastitis increased when Streptococcus dysgalactiae, Streptococcus faecalis, Escherichia coli, or Enterobacter spp. were cultured at drying off and when Escherichia coli, coagulase-positive staphylococcus, Serratia spp., or Streptococcus faecalis were cultured in two out of three late dry and post-calving samples. Quarters from which Corynebacterium spp. were isolated at drying off were at an increased risk of clinical mastitis, whereas the presence of Corynebacterium spp. in the late dry and post-calving samples was associated with a reduction in the risk of clinical mastitis. The risk of mastitis for specific pathogens increased if the same species of bacteria that had caused mastitis was isolated at least twice in the late dry and post-calving samples. Kaplan-Meier survival plots indicated that clinical mastitis associated with dry period infections was more likely to occur earlier in lactation than clinical mastitis not associated with dry period infections. There was evidence of quarter susceptibility to IMI or the possibility that infection with one organism led to clinical mastitis with another.

The impact of clinical lameness on the milk yield of dairy cows

This paper investigates the impact of lameness on milk yield. The dataset includes approximately 8000 test-day milk yields from 900 cows on five farms in Gloucester, UK, collected over 18 mo from 1997 to 1999. The data were structured to account for repeated measures of test-day yield (1 to 10 per cow) and analyzed to account for this autocorrelation. Factors affecting milk yield included: farm of origin, stage of lactation, parity, and whether a cow ever became lame. In clinically lame cows, milk yield was reduced from up to 4 mo before a case of lameness was diagnosed and treated and for the 5 mo after treatment. The total mean estimated reduction in milk yield per 305-d lactation was approximately 360 kg. We conclude that clinical lameness has a significant impact on milk production. This is important information for assessing the economic impact of clinical lameness and its impact on cow health. It adds weight to the importance of early identification of clinical lameness and the urgency of techniques to improve the definition of this highly subjective diagnosis.