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.     

Evaluation of a bulk-milk ELISA test for the classification of herd-level bovine leukemia virus status

The results of a commercial bulk-milk enzyme-linked immunosorbent assay (ELISA) test for herd-level bovine leukemia virus (BLV) status were compared to results obtained from individual agar-gel immunodiffussion (AGID) testing on sampled cattle. A positive herd was defined as a herd having one or more AGID-positive animals. The estimated true herd status was based on the sensitivity and specificity of the AGID test and the number of cattle sampled per herd. Ninety-seven herds were used, with a mean of 13 cows sampled per herd. The AGID test indicated an apparent herd prevalence of 70.1%. After accounting for the number of cows sampled and the sensitivity and specificity of the AGID test, the estimated true herd prevalence of BLV was 52.3%. The ELISA test identified 79.4% of herds as positive for BLV, and had an apparent sensitivity and specificity of 0.97 and 0.62, respectively. However, after accounting for the sensitivity and specificity of the AGID test in individual animals, the specificity of the ELISA test was 0.44. The ELISA test was useful for identifying BLV-negative herds (i.e., ruling out the presence of BLV infection in test negative herds). With the moderately low specificity, herds identified as positive by the ELISA test would require further testing at the individual or herd level to definitively establish their BLV status.     

A practical approach to calculate sample size for herd prevalence surveys

When designing a herd-level prevalence study that will use an imperfect diagnostic test, it is necessary to consider the test sensitivity and specificity. A new approach was developed to take into account the imperfections of the test. We present an adapted formula that, when combined with an existing piece of software, allows improved planning. Bovine paratuberculosis is included as an example infection because it originally stimulated the work. Examples are provided of the trade-off between the benefit (low number of herds) and the disadvantage (large number of animals per herd and exclusion of small herds) that are associated with achieving high herd-level sensitivity and specificity. We demonstrate the bias in the estimate of prevalence and the underestimate of the confidence range that would arise if we did not account for test sensitivity and specificity.     

Simulation model estimates of test accuracy and predictive values for the Danish Salmonella surveillance program in dairy herds

The Danish government and cattle industry instituted a Salmonella surveillance program in October 2002 to help reduce Salmonella enterica subsp. enterica serotype Dublin (S. Dublin) infections. All dairy herds are tested by measuring antibodies in bulk tank milk at 3-month intervals. The program is based on a well-established ELISA, but the overall test program accuracy and misclassification was not previously investigated. We developed a model to simulate repeated bulk tank milk antibody measurements for dairy herds conditional on true infection status. The distributions of bulk tank milk antibody measurements for infected and noninfected herds were determined from field study data. Herd infection was defined as having either >or=1 Salmonella culture-positive fecal sample or >or=5% within-herd prevalence based on antibody measurements in serum or milk from individual animals. No distinction was made between Dublin and other Salmonella serotypes which cross-react in the ELISA. The simulation model was used to estimate the accuracy of herd classification for true herd-level prevalence values ranging from 0.02 to 0.5. Test program sensitivity was 0.95 across the range of prevalence values evaluated. Specificity was inversely related to prevalence and ranged from 0.83 to 0.98. For a true herd-level infection prevalence of 15%, the estimate for specificity (Sp) was 0.96. Also at the 15% herd-level prevalence, approximately 99% of herds classified as negative in the program would be truly noninfected and 80% of herds classified as positive would be infected. The predictive values were consistent with the primary goal of the surveillance program which was to have confidence that herds classified negative would be free of Salmonella infection.     

An estimated prevalence of Johne's disease in a subpopulation of Alabama beef cattle.

The objective of this study was to estimate the overall prevalence of animals that were infected with Mycobacterium avium ssp. paratuberculosis in a subpopulation of Alabama beef cattle. This was determined using a commercial enzyme-linked immunosorbent assay (ELISA) for the detection of M. avium ssp. paratuberculosis-specific antibodies in serum. Serum was collected from 79 herds that were participating in the Alabama Brucellosis Certification program. A total of 2,073 beef cattle were randomly tested by selecting 30 animals per herd in herds greater than 30 and selecting all animals in herds 30 and less for testing. It has been estimated that the commercial ELISA test used has a 60% sensitivity and a 97% specificity. Of the 79 herds tested, 29 herds were seronegative, 24 herds had 1-2 positive animals, and 26 herds had 3 or more seropositive animals. The average number of infected animals per positive herd was 3.3. In addition, a calculated minimum of 53.5% of the herds were identified as Johne's positive herds with a 95% confidence level. Of the total number of animals tested, 8.0% (166/2,073) of them were positive by the ELISA. After adjustments for test sensitivity and specificity and the proportion of animals sampled per herd, the true prevalence was calculated to be 8.75%. These data suggest that approximately 50% of the herds are infected with M. avium ssp. Paratuberculosis, and the overall prevalence of infection in Alabama beef cattle is approximately 8%, which correlates with other previously published regional estimates.     

Herd-level interpretation of test results for epidemiologic studies of animal diseases

Correct classification of the true status of herds is an important component of epidemiologic studies and animal disease-control programs. We review theoretical aspects of herd-level testing through consideration of test performance (herd-level sensitivity, specificity and predictive values), the factors affecting these estimates, and available software for calculations. We present new aspects and considerations concerning the effect of precision and bias in estimation of individual-test performance on herd-test performance and suggest methods (pooled testing, targeted sampling of subpopulations with higher prevalence, and use of combinations of tests) to improve herd-level sensitivity when the expected within-herd prevalence is low.     

A stochastic-modeling evaluation of the foot-and-mouth-disease survey conducted after the outbreak in Miyazaki, Japan in 2000

When foot-and-mouth-disease (FMD) was identified in Miyazaki prefecture in March 2000, Japan conducted an intensive serological and clinical survey in the areas surrounding the index herd. As a result of the survey during the 21 days of the movement-restriction period, two infected herds were detected and destroyed; there were no other cases in the months that followed. To evaluate the survey used for screening the disease-control area and surveillance area, we estimated the herd-level sensitivity of the survey (HSe) through a spreadsheet model using Monte-Carlo methods. The Reed-Frost model was incorporated to simulate the spread of FMD within an infected herd. In the simulations, 4, 8 and 12 effective-contact scenarios during the 5-day period were examined. The estimated HSes of serological tests (HSeE) were 71.0, 75.3 and 76.3% under the 4, 8 and 12 contact scenarios, respectively. The sensitivity analysis showed that increasing the number of contacts beyond 12 did not improve HSeE, but increasing the number of sampled animals and delaying the dates of sampling did raise HSeEs. Small herd size in the outbreak area (>80% of herds have <20 animals) seems to have helped in maintaining HSeE relatively high, although the serological inspection was carried out before sero-positive animals had a chance to increase in infected herds. The estimated herd-level specificity of serological tests (HSpE) was 98.6%. This HSpE predicted 224 false-positive herds (5th percentile estimate was 200 and 95th percentile was 249), which proved close to the 232 false-positive herds actually observed. The combined-test herd-level sensitivity (serological and clinical inspections combined; CTHSe), averaged 85.5, 87.6 and 88.1% for the 4, 8 and 12 contact scenarios, respectively. Using these CTHSes, the calculated probability that no infected herd was overlooked by the survey was > or =62.5% under the most-conservative, four-contact scenario. The probability that no more than one infected herd was overlooked was > or =89.7%.     

A retrospective evaluation of a Bovine Herpesvirus-1 (BHV-1) antibody ELISA on bulk-tank milk samples for classification of the BHV-1 status of Danish dairy herds

Bulk-tank milk samples analysed in a Bovine Herpesvirus-1 (BHV-1) blocking ELISA are still in use in the Danish BHV-1 programme as a tool to classify dairy herds as BHV-1 infected or BHV-1 free herds. In this retrospective study, we used data from the Danish BHV-1 eradication campaign to evaluate performance characteristics of the BHV-1 blocking ELISA in 1039 BHV-1-seropositive and 502 repeatedly BHV-1-negative dairy herds using the results of blood testing of the individual animals as the true infection status. At a cut-off value of 30% blocking reaction, the herd-level relative sensitivity and relative specificity were 82 and 100%, respectively. The herd-level relative sensitivity depended on the within-herd prevalence of seropositive cows and the cut-off value in the assay, but not on the time interval (up to 90 days) between the collection of the bulk-tank milk sample and the individual serum samples. The BHV-1 blocking ELISA on bulk-tank milk could detect seropositive herds (few), with prevalence proportions as low as one seropositive cow out of 70 cows.     

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.     

Prevalence and distribution of paratuberculosis (Johne's disease) in cattle herds in Ireland

A simple random survey was conducted in Ireland during 2005 to estimate the ELISA-prevalence of paratuberculosis, commonly called Johne's disease (JD), in the cattle population. Serum samples were collected from all 20,322 females/breeding bulls over 12 months-of-age in 639 herds. All samples were tested using a commercially available absorbed ELISA. The overall prevalence of infected herds, based on the presence of at least one ELISA-positive animal, was 21.4% (95% CI 18.4%-24.9%). Herd prevalence levels amongst dairy herds (mean 31.5%; 95% CI: 24.6%, 39.3%) was higher than among beef herds (mean 17.9%; 95% CI: 14.6%-21.8%). However, the animal level prevalence was similar. The true prevalence among all animals tested, was calculated to be 2.86% (95%CI: 2.76, 2.97) and for animals >= 2 yrs, it was 3.30% (95%CI: 3.17, 3.43). For animals in beef herds, true prevalence was 3.09% (95%CI: 2.93, 3.24), and for those in dairy herds, 2.74% (95%CI: 2.59, 2.90). The majority of herds had only one ELISA-positive infected animal. Only 6.4% (95% CI 4.7%-8.7%) of all herds had more than one ELISA-positive infected animal; 13.3% (CI 8.7%-19.7%) of dairy herds ranging from two to eight ELISA-positive infected animals; and, 3.9% beef herds (CI 2.4%-6.2%) ranging from two to five ELISA-positive infected animals. The true prevalence of herds infected and shedding Mycobacterium avium subspecies paratuberculosis is estimated to be 9.5% for all herd types; 20.6% for dairy herds; and 7.6% for beef herds. If ELISA positive animals <2-years-of-age are excluded, the true herd prevalene reduces to: 9.3% for all herd types; 19.6% for dairy herds; and 6.3% for beef herds based on a test specificity (Sp) of 99.8% and test sensitivity (Se) (i.e., ability to detect culture-positive, infected animals shedding at any level) of 27.8-28.9%.     

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.     

Herd-level prevalence of Mycobacterium avium subsp. paratuberculosis infection in United States dairy herds in 2007

Testing of composite fecal (environmental) samples from high traffic areas in dairy herds has been shown to be a cost-effective and sensitive method for classification of herd status for Mycobacterium avium subsp. paratuberculosis (MAP). In the National Animal Health Monitoring System's (NAHMS) Dairy 2007 study, the apparent herd-level prevalence of MAP was 70.4% (369/524 had ≥1 culture-positive composite fecal samples out of 6 tested). Based on these data, the true herd-level prevalence (HP) of MAP infection was estimated using Bayesian methods adjusting for the herd sensitivity (HSe) and herd specificity (HSp) of the test method. The Bayesian prior for HSe of composite fecal cultures was based on data from the NAHMS Dairy 2002 study and the prior for HSp was based on expert opinion. The posterior median HP (base model) was 91.1% (95% probability interval, 81.6 to 99.3%) and estimates were most sensitive to the prior for HSe. The HP was higher than estimated from the NAHMS Dairy 1996 and 2002 studies but estimates are not directly comparable with those of prior NAHMS studies because of the different testing methods and criteria used for herd classification.     

Effect of diagnostic testing error on intracluster correlation coefficient estimation

Estimation of the intracluster correlation coefficient (ICC) for infectious animal diseases may be of interest for survey planning and for calculating variance inflation factors for estimators of prevalence. Typically, diagnostic tests with imperfect sensitivity and specificity are used in surveys. In such studies, where animals from multiple herds are tested, the ICC often is estimated using apparent (test-based) rather than true prevalence data. Through Monte Carlo simulation, we examined the effect of substituting diagnostic test outcomes for true infection status on an ANOVA estimator of ICC, which was designed for use with true infection status data. We considered effects of diagnostic test sensitivity and specificity on the estimated ICC when the true ICC value and infection status of the sampled individuals were known. The ANOVA estimator underestimated the true ICC when the diagnostic test was imperfect. We also demonstrated, under the beta-binomial model, that the ICC based on apparent infection status for individuals is < or = ICC based on true infection status. In addition, we propose a Bayesian model for estimating the ICC that incorporates imperfect sensitivity and specificity and illustrate the Bayesian model using a simulation study and one example; a seroprevalence survey of ovine progressive pneumonia in U.S. sheep flocks.     

ELISA and fecal culture for paratuberculosis (Johne's disease): sensitivity and specificity of each method

The sensitivity and specificity of the ELISA and fecal culture tests for paratuberculosis in dairy cattle are examined. ELISA and fecal culture data from seven dairy herds where both fecal cultures and ELISA testing was done concurrently are included. A cohort of 954 cattle including 697 parturient adults, cultured every 6 months from 10 herds followed over 4 years served as the basis to determine fecal culture sensitivity. The fecal culture technique utilized a 2g sample with centrifugation and double incubation. Of the 954 cattle cohort of all ages (calf to adult) that were fecal sampled on the first herd visit, 79 were culture positive. An additional 131 animals were detected as culture positive over the next seven tests at 6-month intervals. The sensitivity of fecal culture to detect infected cattle on the first sampling was 38%. Of the 697 parturient cattle cohort, 67 were positive on the first fecal culture, while an additional 91 adult cattle were culture positive over the next seven tests, resulting in a sensitivity of 42% on the first culture of the total animals identified as culture positive. Animals culled from the herds prior to being detected as infected and animals always fecal culture negative with culture positive tissues at slaughter are not included in the calculations. Both groups of infected cattle will lower the apparent sensitivity of fecal culture. Infected dairy herds tested concurrently with both fecal culture and ELISA usually resulted in more than twofold positive animals by culture compared to ELISA.The classification of infected cattle by the extent of shedding of Mycobacterium paratuberculosis in the feces helps define the relative proportion of cattle in each group and therefore the likelihood of detection by the ELISA test. ELISA has a higher sensitivity in animals with a heavier bacterial load, i.e. high shedders (75%) compared to low shedders (15%). Repeated testing of infected herds identifies a higher proportion of low shedders which are more likely to be ELISA negative. Thus, the sensitivity of the ELISA test decreases with repeated herd testing over time, since heavy shedders will be culled first from the herds.     

Prevalence of paratuberculosis infection in dairy cattle in Northern Italy

Paratuberculosis is a chronic granulomatous infection caused by Mycobacterium avium subsp. paratuberculosis (MAP) that affects multiple ruminant species causing important economic losses. Therefore, control programmes at herd and regional levels have been established worldwide and prevalence estimates are needed for their implementation. Although different herd-level prevalence estimations for paratuberculosis have been reported in Europe, very few studies provided comparable and interpretable values, due to poor study designs and lack of knowledge about the accuracy of the diagnostic tests used. To overcome these problems we applied a latent class analysis to the results of two prevalence studies carried out in two neighbouring Northern Italian regions (Lombardy and Veneto) that account for over 50% of the Italian dairy cattle population. Serum samples from a randomly selected number of farms in the two regions were analyzed by different ELISA tests. The herd-level Apparent Prevalences (AP) were 48% (190/391) for Lombardy and 65% (272/419) for Veneto. Median within-herd APs were 2.6% and 4.0% for Lombardy and Veneto, respectively. Posterior estimates for the herd-level True Prevalences (TP) based on a Bayesian model were very similar between the two regions (70% for Lombardy and 71% for Veneto) and close to previous estimates of infected herds in Europe. The two 95% credibility intervals overlap each other, virtually showing only one distribution of the herd-level true prevalence for both regions. On the contrary, estimates of the within-herd TP distributions differed between the two regions (mean values: 6.7% for Lombardy and 14.3% for Veneto), possibly due to the different age distribution within the herds from the two regions.     

Cut-off points for aggreate herd testing in the presence of disease clustering and correlation of test errors

In order to test if disease is present in a large herd, an investigator will often subject only a small sample of animals to a fallible diagnostic test. The herd is declared positive for disease if the number of test-positive animals is greater than or equal to a previously chosen cut-off value. Such a test, called an aggregate test, has a sensitivity and specificity that depends on the sample size, the cut-off point and the sensitivity and specificity of the individual test. It also depends on the distribution of the disease among the herds being tested and on the fact that factors such as herd-level seropositivity may cause some herds to be more prone to testing errors than others. In this paper, we use the beta-binomial distribution to model all these factors and thereby calculate and tabulate aggregate test sensitivities and specificities under a variety of conditions. Receiver operating characteristic (ROC) curve methodology permits the choice of optimum sample sizes and cut-off values. We also investigate the situation in which an investigator may be willing to miss detecting the disease if the prevalence in the herd is low. A compiled FORTRAN program for the calculation of aggregate test cut-off point properties, including positive and negative predictive values, is available from the authors.     

Associations between farm management practices, productivity, and bovine leukemia virus infection in Ontario dairy herds

The objective of this study was to investigate the associations between herd-level bovine leukemia virus (BLV) status and herd-level management and production variables. The study population consisted of 1330 cows sampled from 102 Ontario dairy herds. The individual-cow prevalence of BLV infection in the population (based on AGID testing) was 23%, with 69.6% of herds having one or more positive animals. The herd-level explanatory variables were divided into two datasets containing winter housing variables and all non-seasonal variables, and summer housing variables and all non-seasonal variables. In both datasets, multivariable analyses found a negative association between herd-level milk production and BLV status, and positive associations between weaning age and purchasing animals from outside sources, and BLV status. Housing pre-weaned calves in hutches or separate calf buildings in either season was associated with an increased risk of BLV. The model containing winter housing variables also included positive associations between contact with older animals and BLV status, and between BLV status and the facilities used to house dry cows in the winter.     

A serological survey for bovine immunodeficiency-like virus in Ontario dairy cattle and associations between test results, production records and management practices.

A chemiluminescence Western blot analysis (WBA) for detecting antibovine immunodeficiency-like virus (BIV) antibodies, had good repeatability. The test was subsequently applied to a bank of serum samples from 928 adult cows from 265 herds in Ontario; the number of cows sampled within each herd ranged from 1 to 13. The overall prevalence of anti-BIV antibodies among cows was 5.5% with a 95% confidence interval of 4.2% to 7.2%. In contrast, 18.1% of herds had at least one reactor among cows tested, resulting in a herd-prevalence confidence interval of 13.8% to 23.4%. These estimates of prevalence were in the same range as previous reports from the US and Europe. Bovine immunodeficiency-like virus may have a worldwide distribution. Unfortunately, BIV test sensitivity and specificity are difficult to estimate because virus isolation is inefficient. Therefore, the apparent prevalences could not be adjusted for test sensitivity and specificity, to estimate the true prevalence of infection. The serum samples had previously been tested for antibodies to bovine leukemia virus (BLV). There were no significant associations between BIV and BLV test results. Least squares regression was used to investigate potential associations between BIV test results and selected production indices.(ABSTRACT TRUNCATED AT 250 WORDS)     

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).     

Evaluation of two herd-level diagnostic tests for Streptococcus agalactiae using a latent class approach

Streptococcus agalactiae mastitis persists as a significant economic problem for the dairy industry in many countries. In Denmark, the annual surveillance programme for this mastitis pathogen initially based only on bacteriological culture of bulk tank milk (BTM) samples, has recently incorporated the use of the real-time PathoProof Mastitis PCR assay with the goal of improving detection of infected herds. The objective of our study was to estimate the herd sensitivity (Se) and specificity (Sp) of both tests of BTM samples using latent class models in a Bayesian analysis while evaluating the effect of herd-level covariates on the Se and Sp of the tests. BTM samples were collected from all 4258 Danish dairy herds in 2009 and screened for the presence of S. agalactiae using both tests. The highest Se of PCR was realized at a cycle threshold (Ct) cut-off value of 40. At this cut-off, the Se of the PCR was significantly higher (95.2; 95% posterior credibility interval [PCI] [88.2; 99.8]) than that of bacteriological culture (68.0; 95% PCI [55.1; 90.0]). However, culture had higher Sp (99.7; 95% PCI [99.3; 100.0]) compared to PCR (98.8; 95% PCI [97.2; 99.9]). The accuracy of the tests was unaffected by the herd-level covariates. We propose that screenings of BTM samples for S. agalactiae be based on the PCR assay with Ct readings of <40 considered as positive. However, for higher Ct values, confirmation of PCR test positive herds by bacteriological culture is advisable especially when the between-herd prevalence of S. agalactiae is low.