The need for built-in validation of surveillance data so that changes in diagnostic performance of post-mortem meat inspection can be detected

Time trends in animal-disease surveillance often are evaluated on the basis of crude estimates of apparent prevalence. In addition to possible changes in the true prevalence of the condition, changes in apparent prevalence over time might reflect changes in sensitivity and/or specificity of the diagnostic classification used. To illustrate this, comparative post-mortem meat inspection data from four Danish slaughter plants sampled in 1993-1994 and 1997-1998 were used to obtain latent-class model estimates of the sensitivity and specificity of traditional and extended post-mortem meat inspection of visceral and parietal chronic pleuritis (CP), respectively.True prevalence of CP was estimated for each study period and slaughter plant by latent-class models. Estimated sensitivities of traditional post-mortem meat (TPM) inspection ranged from 28.8 to 61.4% (1993-1994) and 39.2 to 87.3% (1997-1998). An increase in sensitivity with time was seen for all slaughter plants. Estimated sensitivities of extended post-mortem meat (EPM) inspection ranged from 85.7 to 94.8% (1993-1994) and 73.8 to 93.0% (1997-1998). All estimated specificities were >93.3%.The possible association of the estimated true prevalence of CP with time (1993-1994 versus 1997-1998) was investigated with a logistic-regression model with random effects. A slight, but non-significant decrease in the odds of CP from 1994 to 1998 was found (odds ratio=0.9).In this and similar situations, one should consider conducting ongoing double-classification of samples of units followed by statistical estimation of true prevalences, sensitivities and specificities, so that decisions can be based on such estimates rather than on crude apparent prevalences.     

Management-related risk factors for M. paratuberculosis infection in Michigan, USA, dairy herds

A cross-sectional study was conducted from June through December 1996 to identify management-related risk factors for herd-level M. paratuberculosis infection. Data were collected from 121 participating herds. A two-part questionnaire was administered to gather data on current and previous management practices and herd productivity. A random sample of cows aged ≥24 months was selected from each herd and tested for antibodies to M. paratuberculosis using the IDEXX Antibody ELISA (sensitivity 64%, specificity 96%). A positive herd was one in which ≥2 animals tested positive for antibodies to M. paratuberculosis. A negative herd was one in which no animal tested positive. Herds in which only one animal tested positive were dropped from statistical analysis to reduce the risk of including false-positive herds in the statistical analyses.

There were 80 herds with one or more positive animals and 41 herds with no positive animals in the sample (66% herd-level prevalence). Twenty-six herds (21%) were dropped from further analyses because they had only one positive cow. Twelve herds (10%) were dropped from analysis because of missing data. The resulting sample used for statistical modeling included 46 positive herds and 37 negative herds (55% herd-level prevalence). A multi-variable logistic-regression model was used to evaluate the results. The variable ‘use of an exercise lot for lactating cows' was associated with a three-fold increase in odds of a herd being positive for M. paratuberculosis infection (O.R.=3.01, C.I.=1.03–8.80); ‘cleaning of maternity pens after each use' was associated with a three-fold reduction in odds of a herd being positive for M. paratuberculosis infection (O.R.=0.28, C.I.=0.08–0.89); ‘application of lime to pasture areas in 1993' resulted in a ten-fold decrease in odds of a herd being positive for M. paratuberculosis infection (O.R.=0.10, C.I.=0.02–0.56).     

Risk factors for digital dermatitis in dairy cows kept in cubicle houses in The Netherlands

The presence of digital dermatitis (DD) in dairy cows has increased considerably over the last 10 years in The Netherlands, resulting in a current prevalence of approximately 30% in cows kept in cubicle houses. Our objective was to evaluate a diversified sample of cow- and herd-related risk factors for DD in dairy cows housed in cubicle houses with different flooring systems. Associations were analysed in random-effects logistic-regression models using 2,134 cows (37 herds) and 2,892 cows (47 herds) in the pasture and housing studies, respectively. At cow-level, the odds of having DD were increased in the case of lower parity and lactation. Important risk factors at herd-level were: restricted grazing time, fast rise in concentrate amount after calving, feeding by-products, herd trimming only at long intervals, and introduction of dry cows into the lactating herd before calving. The odds for DD were lower if cows were housed on a slatted floor with manure scraper and provided long and wide cubicles, and if calves were reared in the dairy cows' accommodation.     

Associations of Neospora caninum seropositivity with gestation number and pregnancy outcome in Danish dairy herds.

The prevalence and distribution of seropositivity towards the protozoan parasite Neospora caninum were studied in single blood samples from 1561 cows from 31 Danish dairy herds. Blood samples were analysed by an indirect enzyme-linked immunoassay and an indirect fluorescent-antibody test. Seroprevalence in 15 herds with previous abortions assigned to neosporosis ranged from 1% to 58%, with a mean frequency of 22%. In eight out of 16 herds without a history of N. caninum related abortions, no seroreactors were found. In the remaining eight herds, the seroprevalence ranged from 6% to 59%. The prevalence and distribution of seropositivity, gestation number prior to sampling, and breed were related to abortions and perinatal deaths using a random-effects logistic-regression model. Abortion risk was significantly increased in seropositive animals (OR=3) and in 2nd-gestation cows (OR=3). Perinatal death was significantly influenced by gestation number and breed, but not by serostatus. Reproductive performance and culling risk of cows were not affected by serostatus. Seropositivity increased with “age” (i.e. gestation number) (P=0.02). In open cows, seropositivity tended to decrease with distance from calving (P=0.05). The proportion of seropositive pregnant cows increased with trimester (P=0.02).     

Adjusting for heterogeneity of experimental data in genetic evaluation of dry matter intake in dairy cattle

The objectives of the present study were (i) to find the best fitted model for repeatedly measured daily dry matter intake (DMI) data obtained from different herds and experiments across lactations and (ii) to get better estimates of the genetic parameters and better genetic evaluations. After editing, there were 572,512 daily DMI records of 3,495 animals (Holstein cows) from 11 different herds across 13 lactations and the animals were under 110 different nutritional experiments. The fitted model for this data set was a univariate repeated‐measure animal model (called model 1) in which additive genetic and permanent environmental (within and across lactations) effects were fitted as random. Model 1 was fitted as two distinct models (called models 2 and 3) based on alternative fixed effect corrections. For unscaled data, each model (models 2 and 3) was fitted as a homoscedastic (HOM) model first and then as a heteroscedastic (HET) model. Then, data were scaled by multiplying with particular herd‐scaling factors, which were calculated by accounting for heterogeneity of phenotypic within‐herd variances. Models were selected based on cross‐validation and prediction accuracy results. Scaling factors were re‐estimated to determine the effectiveness of accounting for herd heterogeneity. Variance components and respective heritability and repeatability were estimated based on a pedigree‐based relationship matrix. Results indicated that the model fitted for scaled data showed better fit than the models (HOM or HET) fitted for unscaled data. The heritability estimates of the models 2 and 3 fitted for scaled data were 0.30 and 0.08, respectively. The repeatability estimates of the model fitted for scaled data ranged from 0.51 to 0.63. The re‐estimated scaling factor after accounting for heterogeneity of residual variances was close to 1.0, indicating the stabilization of residual variances and herd accounted for most of the heterogeneity. The rank correlation of EBVs between scaled and unscaled data ranged from 0.96 to 0.97.     

Bayesian mixture models for within-herd prevalence estimates of bovine paratuberculosis based on a continuous ELISA response

Diagnostic inference by use of assays such as ELISA is usually done by dichotomizing the optical density (OD)-values based on a predetermined cut-off. For paratuberculosis, a slowly developing infection in cattle and other ruminants, it is known that laboratory factors as well as animal specific covariates influence the OD-value, but while laboratory factors are adjusted for, the animal specific covariates are seldom utilized when establishing cut-offs. Furthermore, when dichotomizing an OD-value, information is lost. Considering the poor diagnostic performance of ELISAs for diagnosis of paratuberculosis, a framework for utilizing the continuous OD-values as well as known coavariates could be useful in addition to the traditional approaches, e.g. for estimating within-herd prevalences.

The objective of this study was to develop a Bayesian mixture model with two components describing the continuous OD response of infected and non-infected cows, while adjusting for known covariates. Based on this model, four different within-herd prevalence indicators were considered: the mean prevalence in the herd; the age adjusted prevalence of the herd for better between-herd comparisons; the rank of the age adjusted prevalence to better compare across time; and a threshold-based prevalence to describe differences between herds. For comparison, the within-herd prevalence and associated rank using a traditional dichotomization approach based on a single cut-off for an OD corrected for laboratory variation was estimated in a Bayesian model with priors for sensitivity and specificity.

The models were applied to the OD-values of a milk ELISA using samples from all lactating cows in 100 Danish dairy herds in three sampling rounds 13 months apart. The results of the comparison showed that including covariates in the mixture model reduced the uncertainty of the prevalence estimates compared to the cut-off based estimates. This allowed a more informative ranking of the herds where low ranking and high ranking herds were easier to identify.     

Prevalence of Trypanosoma evansi infection and associated risk factors in camels in eastern Chad

A cross-sectional study was conducted to estimate the prevalence of Trypanosoma evansi infection (Surra) in herds of camels from the eastern area of Chad. The risk factors associated with disease were also identified. From August 1997 to April 1998, a random sample of 2831 camels from 136 herds was selected. Blood samples were collected and examined for the presence of T. evansi using an antibody (card agglutination test-CATT/T. evansi) and a parasite detection test (buffy-coat technique-BCT). Standardized questionnaires with information about the host and management practices were collected and evaluated for their association with seroprevalence (model 1) and parasitological prevalence (model 2) as indications of host sensitivity. In both models, risk factors were selected using ordinary logistic regression (OLR) and herd effect was evaluated using a generalized estimating equations (GEE) model. The apparent prevalence was 5.3% using BCT and 30.5% with CATT. Real prevalence was estimated at 16.9% +/- 1.4 (alpha = 5%). Overall, 27.9% (BCT) and 94.9% (CATT) of the herds had a least one-positive animal. Real herd prevalence was estimated at 42.6 +/- 8.3% (alpha = 5%). Camels of the large transhumants had the highest prevalence (estimated to 30.3% +/- 2.5; 62.9 +/- 12.0 in herds). Risk factors associated with seroprevalence were age, ethnic group, length of seasonal migration and longitude of pasture area in the dry season. Risk factors associated with BCT prevalence were age, length of seasonal migration, longitude of pasture area in the dry season, latitude of pasture area in the rainy season and season of sampling.     

Associations of Neospora caninum seropositivity with gestation number and pregnancy outcome in Danish dairy herds

The prevalence and distribution of seropositivity towards the protozoan parasite Neospora caninum were studied in single blood samples from 1561 cows from 31 Danish dairy herds. Blood samples were analysed by an indirect enzyme-linked immunoassay and an indirect fluorescent-antibody test. Seroprevalence in 15 herds with previous abortions assigned to neosporosis ranged from 1% to 58%, with a mean frequency of 22%. In eight out of 16 herds without a history of N. caninum related abortions, no seroreactors were found. In the remaining eight herds, the seroprevalence ranged from 6% to 59%. The prevalence and distribution of seropositivity, gestation number prior to sampling, and breed were related to abortions and perinatal deaths using a random-effects logistic-regression model. Abortion risk was significantly increased in seropositive animals (OR=3) and in 2nd-gestation cows (OR=3). Perinatal death was significantly influenced by gestation number and breed, but not by serostatus. Reproductive performance and culling risk of cows were not affected by serostatus. Seropositivity increased with “age” (i.e. gestation number) (P=0.02). In open cows, seropositivity tended to decrease with distance from calving (P=0.05). The proportion of seropositive pregnant cows increased with trimester (P=0.02).     

Bayesian modeling of animal- and herd-level prevalences

We reviewed Bayesian approaches for animal-level and herd-level prevalence estimation based on cross-sectional sampling designs and demonstrated fitting of these models using the WinBUGS software. We considered estimation of infection prevalence based on use of a single diagnostic test applied to a single herd with binomial and hypergeometric sampling. We then considered multiple herds under binomial sampling with the primary goal of estimating the prevalence distribution and the proportion of infected herds. A new model is presented that can be used to estimate the herd-level prevalence in a region, including the posterior probability that all herds are non-infected. Using this model, inferences for the distribution of prevalences, mean prevalence in the region, and predicted prevalence of herds in the region (including the predicted probability of zero prevalence) are also available. In the models presented, both animal- and herd-level prevalences are modeled as mixture distributions to allow for zero infection prevalences. (If mixture models for the prevalences were not used, prevalence estimates might be artificially inflated, especially in herds and regions with low or zero prevalence.) Finally, we considered estimation of animal-level prevalence based on pooled samples.     

Bayesian estimation of true between-herd and within-herd prevalence of Salmonella in Danish veal calves

Specialised veal producers that purchase and raise calves from several dairy herds are potentially at high risk of delivering Salmonella-infected animals to slaughter. However, the true prevalence of Salmonella infected veal producing herds and the prevalence of infected calves delivered to slaughter from infected herds are unknown in Denmark. Due to uncertainties about test sensitivity and specificity, these prevalences are not straightforward to assess. The objective of this study was to estimate the within-herd- and between-herd prevalence of Salmonella in veal calves delivered for slaughter to abattoirs in Denmark. Furthermore, it was investigated to which extent the estimates differed between a setup using both serological tests and faecal culture, compared to just serological tests, and whether the applied sampling scheme in the national surveillance programme in Denmark was sufficient to establish high posterior estimates of freedom from infection in individual herds. We used Bayesian analysis to avoid bias as a result of fixed test validity estimates. Serological test results from 753 animals and faecal culture from 1233 animals from 68 randomly selected Danish veal producing herds that delivered more than 100 calves to slaughter per year were used to estimate the prevalences and estimates of freedom from Salmonella. Serological test results of 7726 animals from 185 herds were used to compare the difference in prevalence estimates between serology alone vs. faecal culture combined with serology. We estimated that 34-57% of specialised veal producing herds were infected with Salmonella. Within the infected herds, 21-49% of the animals were infected. Few herds obtained high posterior estimates for the probability of freedom from infection given the collected data, with only six of 68 herds obtaining posterior probability of being infected less than 10%. Furthermore, this study indicated that serology is sufficiently sensitive and specific to be used for estimating the prevalence of Salmonella-infected specialised veal producing herds.     

A Bayesian approach to the accuracy of clinical observations

The accuracy of clinical observations was estimated using Bayesian latent-class models with two or more independent tests. Four veterinarians carried out systematic independent clinical examinations on 155 pigs in three herds. Based on the results of binary recordings of clinical observations on dullness, poor body condition (PBC), skin lesions, lameness, respiratory disease, and diarrhea, a latent disease state for each clinical disease was estimated using Gibbs sampling.

The accuracy of the clinical observations differed for the four observers and for different clinical signs. Population parameters were estimated from a Bayesian hierarchical model, and the accuracy of a random observer was calculated. We concluded that the accuracy of the veterinarians in this study substantiated the need to pursue more-precise definitions of the clinical findings and that larger sample sizes would be needed to provide reasonable variance estimates. Finally, we concluded that the uncertainty in the clinical decision-making process (starting with the clinical examination) needs to be represented fully.     

Evaluation models and genetic parameters for calving difficulty in beef cattle

Calving difficulty was analyzed under threshold and linear models considering either a fixed or random herd-year effect. The aim of the study was to compare models for predicting breeding values according to the size of herd-year groups. When simulating data sets with small herds, in order to obtain an unbiased evaluation under a nonrandom and negative association of sire and herd effects, the best model for a practical evaluation was the fixed linear model. Field data included 246,576 records of the largest Charolais herds in France. Models were compared using the correlations of estimated breeding values between the different models. Although the best model from a theoretical point of view was a threshold model with a fixed herd-year effect, a linear model with a fixed herd-year effect was the best choice from a practical point of view for predicting direct effects for calving difficulty in beef cattle and was a sufficient choice for predicting the associated maternal effects for data set with large herds. Correlations between direct estimated breeding values under the reference model and the fixed linear model and the random threshold model were 0.94 and 0.91, respectively. Correlations between the corresponding maternal estimated breeding values were 0.94 and 0.98. Heritabilities of direct effects were 0.27 and 0.14 under fixed threshold and fixed linear models, respectively. The corresponding heritabilities of maternal effects were 0.18 and 0.13, and the genetic correlation between direct and maternal effects were -0.36 and -0.34, respectively.     

The range of influence between cattle herds is of importance for the local spread of Salmonella Dublin in Denmark

The objective of the study was to estimate the range of influence between cattle herds with positive Salmonella Dublin herd status. Herd status was a binary outcome of high/low antibody levels to Salmonella Dublin in bulk-tank milk and blood samples collected from all cattle herds in Denmark for surveillance purposes. Two methods were used. Initially, a spatial generalised linear mixed model was developed with an exponential correlation function to estimate the range of influence simultaneously with the effect of potential risk factors. An iteratively reweighted generalised least squares procedure was used as a second method for verifying the range of influence estimates. With this iterative procedure, deviance residuals were calculated based on a generalised linear model and the range of influence was estimated based on the residuals using an exponential semivariogram. The range of influence was estimated for six different regions in Denmark using both methods. The analyses were performed on data collected during 1 year after initiation of the Salmonella Dublin surveillance program providing herd classifications for the 4th year-quarter of 2003 and 2 years later for the 4th year-quarter of 2005. The prevalence of dairy herds with a positive Salmonella Dublin herd classification status in this period had decreased from 22.1 to 17.0%. In non-dairy herds, the prevalence was nearly unchanged during the same period (3.4 and 3.7% in 4th quarter of 2003 and 2005, respectively). For all cattle herds, the range of influence was 2.3–6.4 km in 2003 and 1.5–8.3 km in 2005. There seemed to be no association between the range of influence and the density of herds in the different regions.     

The range of influence between cattle herds is of importance for the local spread of Salmonella Dublin in Denmark

The objective of the study was to estimate the range of influence between cattle herds with positive Salmonella Dublin herd status. Herd status was a binary outcome of high/low antibody levels to Salmonella Dublin in bulk-tank milk and blood samples collected from all cattle herds in Denmark for surveillance purposes. Two methods were used. Initially, a spatial generalised linear mixed model was developed with an exponential correlation function to estimate the range of influence simultaneously with the effect of potential risk factors. An iteratively reweighted generalised least squares procedure was used as a second method for verifying the range of influence estimates. With this iterative procedure, deviance residuals were calculated based on a generalised linear model and the range of influence was estimated based on the residuals using an exponential semivariogram. The range of influence was estimated for six different regions in Denmark using both methods. The analyses were performed on data collected during 1 year after initiation of the Salmonella Dublin surveillance program providing herd classifications for the 4th year-quarter of 2003 and 2 years later for the 4th year-quarter of 2005. The prevalence of dairy herds with a positive Salmonella Dublin herd classification status in this period had decreased from 22.1 to 17.0%. In non-dairy herds, the prevalence was nearly unchanged during the same period (3.4 and 3.7% in 4th quarter of 2003 and 2005, respectively). For all cattle herds, the range of influence was 2.3–6.4 km in 2003 and 1.5–8.3 km in 2005. There seemed to be no association between the range of influence and the density of herds in the different regions.     

Success at first insemination in Australian Angus cattle: analysis of uncertain binary responses

Field data from Australian Angus herds were used to investigate 2 methods of analyzing uncertain binary responses for success or failure at first insemination. A linear mixed model that included herd, year, and month of mating as fixed effects; unrelated service sire, additive animal, and residual as random effects; and linear and quadratic effects of age at mating as covariates was used to analyze binary data. An average gestation length (GL) derived from artificial insemination data was used to assign an insemination date to females mated to natural service sires. Females that deviated from this average GL led to uncertain binary responses. Two analyses were carried out: 1) a threshold model fitted to uncertain binary data, ignoring uncertainty (M1); and 2) a threshold model fitted to uncertain binary data, accounting for uncertainty via fuzzy logic classification (M2). There was practically no difference between point estimates obtained from M1 and M2 for service sire and herd variance; however, when uncertain binary data were analyzed ignoring uncertainty (M1), additive variance and heritability estimates were greater than with M2. Pearson correlations indicated that no major reranking would be expected for service sire effects and animal breeding values using M1 and M2. Given the results of the current study, a threshold model contemplating uncertainty is suggested for noisy binary data to avoid bias when estimating genetic parameters.     

Effects of sustained control of brushtail possums on levels of Mycobacterium bovis infection in cattle and brushtail possum populations from Hohotaka, New Zealand

AIMS: To examine the effect of reducing the abundance of brushtail possums (Trichosurus vulpecula) on the distribution and prevalence of bovine tuberculosis (Mycobacterium bovis, Tb) in possums and the incidence of Tb in domestic cattle on a group of farms in the central North Island, New Zealand. METHODS: The cumulative yearly incidence of Tb infection from 12 cattle herds was estimated from annual tuberculin testing and abattoir inspection data over the period 1983-98. Intensive control of possum populations began for six of the herds in 1988, five herds in 1994 and the remaining herd in 1996. The prevalence and distribution of macroscopic M. bovis infection in possums and an index of possum abundance was estimated during yearly cross-sectional surveys from 1988 to 1998. This enabled formal testing of the link between the abundance of tuberculous possums and the incidence of Tb in cattle. RESULTS: Before possum control, infected possums were clustered in foci on or adjacent to the farms with the highest annual incidence of tuberculosis in cattle, and had an overall prevalence of macroscopic M. bovis infection of 2.3%. The prevalence of disease declined to zero with ongoing possum control, although infected possums continued to be found during the first 5 years of control. Maintaining the possum population at an average of 22.1% of its pre-control density significantly reduced the odds of the cumulative yearly incidence of Tb in cattle by 77% during the first 5 years of possum control and a further 65% in the second 5-year period. Nine of 11 tuberculous possums identified since the start of possum control were found within the areas where infected possums were clustered during the pre-control survey, suggesting that the persistence of infection within these clusters rather than infected immigrants was the source of ongoing disease. Annual estimates of the prevalence of tuberculous possums broadly followed the predictions of Barlow's possum-Tb model for a controlled possum population. CONCLUSION: The results support the hypothesis that tuberculous possums transmit bovine tuberculosis to domestic cattle, and therefore that reducing the abundance of tuberculous possums reduces the incidence of Tb in cattle. If the level of possum culling is sufficient, it appears that M. bovis infection may be eradicated from possum populations. Better information on population density, rate of increase and annual culling rates would have been needed for a truly independent examination of the Barlow possum-Tb model.     

Simulation model of within-herd transmission of bovine tuberculosis in Argentine dairy herds

Transmission of bovine tuberculosis was quantified in three dairy herds located in south Santa Fe Province, Argentina. Using estimates of Mycobacterium bovis transmission (β) and a Reed–Frost simulation model, the prevalence of tuberculosis infection in the study herds over time was investigated. The Reed–Frost model was modified by incorporating randomness in both β and the incubation period () of M. bovis. The mean estimated herd β was 2.2 infective contacts per year and did not differ significantly between the study herds. Modeling as Poisson distributed (mean 24 months) best fit the observed prevalences. Infection was predicted by the model either to spread quickly (<10 years) within a herd and reach a high prevalence (>50%), or to persist at a low prevalence (<5–10%). The model was robust, predictions were realistic and the mean β estimated was consistent with previous studies of bovine tuberculosis.     

Bayesian analysis to validate a commercial ELISA to detect paratuberculosis in dairy herds of southern Chile

In Chile, Mycobacterium avium subsp. paratuberculosis (Map) has been isolated on several occasions and clinical cases have been reported. Nevertheless, diagnostic tests have not yet been validated for this agent in the Chilean setting. The objective of the study was to validate a commercial ELISA to detect Map shedding dairy cows in management conditions, prevalence and stages of infection existing in Southern Chile, utilising different statistical approaches. Blood and faeces were collected from 1333 lactating cows in 27 dairy herds (both large commercial and smallholder dairy farms) between September 2003 and August 2004. Within the herds up to a maximum of 100 dairy cows were selected based on age (>or=3 years old) and, if present, clinical signs of a Map infection. In herds with less than 100 cows, all cows >or=3 years old were sampled. Blood samples were tested using a commercial ELISA kit (IDEXX Laboratories, Inc.). Faecal samples were cultured on Herrold's Egg Yolk Medium (HEYM). Latent class models (i.e. maximum likelihood (ML) methods and Bayesian inference) were used to determine the validity of the ELISA. Map was cultured from 54 (4.1%) cows and 10 (37.0%) herds, which were all large, commercial dairy herds. As a result of empty cells in the cross-tabulations, the ML model provided the same results as the validation with faecal culture as the gold-standard. In the Bayesian model, the Se and Sp of the ELISA were estimated to be 26% (95% CI: 18-35%) and 98.5% (95% CI: 97.4-99.4%), respectively. For faecal culture, the Se was 54% (95% CI: 46-62%) and the Sp was 100% (95% CI: 99.9-100%). Interestingly, the prevalence in the smallholder dairy farms was estimated to be 8% even though there were no faecal culture positive cows detected in those herds. There was no significant correlation between the two tests. The advantage of Bayesian inference is that the Se and Sp of both tests are obtained in one model relative to the (latent) true disease status, the model can handle small datasets and empty cells and the estimates can be corrected for the correlation between tests when the tests are not conditionally independent. Therefore, Bayesian analysis was the preferred method for Map that lacks a gold-standard and usually has low cow-level prevalence.     

Genetic variation in serological response to Mycobacterium avium subspecies paratuberculosis and its association with performance in Irish Holstein–Friesian dairy cows

Paratuberculosis, also referred to as Johne's disease, is a contagious and chronic disease in ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). Few estimates of the genetic variation in measures of susceptibility to MAP are available in the literature and even less have attempted to elucidate the genetic associations between measures of susceptibility to MAP and performance in dairy cattle. The objectives of this study were to estimate the genetic variation in serological response to MAP in 4789 Holstein–Friesian dairy cows from 44 Irish dairy herds, and to quantify its genetic association with performance traits measured in the first three lactations of genetically related animals. Univariate mixed linear and threshold animal models were used to estimate variance components and genetic correlations were estimated using bivariate animal linear mixed models; MAP serological response was treated as a continuous variable and dichotomous variable. The prevalence of MAP in the sample population was 4.4%. This figure cannot be extrapolated to the national dairy herd as the sample population was biased towards herds with increased likelihood of MAP infection. Estimates of heritability for MAP serological response varied from 0.07 to 0.15 depending on the model of analysis and whether serological response was treated as continuous or binary; standard errors varied from 0.024 to 0.062. Genetic correlations between MAP serological response and lactation milk, fat and protein yield were negative or close to zero although not always more than two standard errors from zero; stronger negative genetic correlations were evident in older parity animals. Serological response to MAP was not genetically correlated with milk fat concentration but was positively genetically correlated with milk protein concentration in first lactation and negatively correlated with calving interval. There was little or no genetic association between serological response to MAP and survival. Results from this study corroborate previous international suggestions that selection for reduced serological response to MAP is possible, although this does not necessarily imply a concurrent selection for either reduced prevalence of clinical disease or increased resistance to MAP infection.     

Epidemiology of Trypanosoma vivax infection in cattle in the tse-tse free area of Lake Chad

A study was conducted in Chad to estimate the prevalence and the incidence of Trypanosoma vivax infection in herds of cattle from the Lake Chad area. The risk factors associated with disease were also identified. A random sample of 933 cattle from 17 herds was initially selected (January 1999, cold dry season). Cattle were identified by ear-tags and sampled in the rainy season (July 1999) and the cold dry season (January 2000). Each animal sampled was treated with diminazene aceturate (3.5mg/kg). Samples were examined for the presence of T. vivax using an antibody (indirect ELISA) and a parasite detection test (buffy-coat technique, BCT). Standardized questionnaires with information about the host and management practices were collected and evaluated for their association with seroprevalence (model 1) and parasitological prevalence (model 2) as indicator of host susceptibility to T. vivax infection. Risk factors were selected using two approaches: ordinary logistic regression (OLR) and generalized estimating equations (GEE) to account for within-herd correlation. The apparent prevalence was 1.6% using BCT and 42.3% with indirect ELISA. The true prevalence in the sample was estimated to (2.0%-8.0%) with two assumptions of BCT sensitivity. Overall, 58.8% (BCT) and 100.0% (ELISA) of the herds had a least one-positive animal. In January-July 1999, apparent monthly incidence was calculated at 0.24% in comparison with 0.76% for August 1999-January 2000. The true monthly incidence was estimated at 0.36%-1.43% for the first period and at 0.94%-3.78% for the second period. Risk factors associated with seroprevalence were age, race, a great number of small ruminants in the herd, and latitude and longitude of pasture area in the rainy season. Risk factors associated with BCT prevalence were duration of seasonal migration and longitude of pasture area in the rainy season. In conclusion, T. vivax is present and widely disseminated in the cattle herds of tse-tse free area of Lake Chad. Farm-level factors, particularly seasonal migration, should be considered as the main risk factors for infection and to host susceptibility to the parasite.