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A total of 854 paired milk and blood samples were collected from ewes of a Greek flock and used to estimate the sensitivity and specificity of a commercial ELISA for detection of Mycobacterium avium subsp. paratuberculosis (MAP) specific antibodies in each stage of lactation. We implemented Bayesian mixture models to derive the distributions of the test response for the healthy and the infected ewes. In the colostrum period, early, mid and late lactation stage the median values of the area under the curves (AUC) were 0.61 (95% credible interval: 0.50; 0.84), 0.61 (0.51;0.84), 0.65 (0.51;0.91), 0.65(0.51;0.89) for the serum ELISA and and 0.60 (0.50; 0.84), 0.61 (0.50; 0.84), 0.67(0.51; 0.91), 0.66(0.50; 0.90) for the milk ELISA, respectively. Both serum and milk ELISA had low to average overall discriminatory ability as measured by the area under the curves and comparable sensitivities and specificities at the recommended cutoffs., (Copyright © 2015 Elsevier B.V. All rights reserved.)

In this cross-sectional study we identified flock-level risk factors for Mycobacterium avium subsp. paratuberculosis (MAP) infection, in Greek dairy goat flocks. We collected 1599 milk samples from does that were at the last stage of lactation in 58 randomly selected dairy goat flocks, during May to September 2012. The collected samples were tested with a commercial milk ELISA (IdexxPourquier, Montpellier, France) and the results were interpreted at a cut-off that optimized the accuracy of the diagnostic process. For the analysis of the data we used Bayesian models that adjusted for the imperfect Se and Sp of the milk-ELISA. Flock was included as a random effect. Does in flocks that used common water troughs and communal grazing grounds had 4.6 [95% credible interval (CI): 1.5; 17.4] times higher odds of being MAP-infected compared to does in flocks that had no contact with other flocks. Does of flocks supplied with surface water from either streams or shallow wells had 3.7 (1.4; 10.4) times higher odds of being infected compared to those in flocks watered by underground and piped water sources. When kids were spending equal to or more than 10h per day with their dams they had 2.6 (1.1; 6.4) times higher odds of being MAP infected compared to kids that were separated from their dams for less than 10h per day. Finally, does in flocks that continuously used the same anti-parasitic compound had 2.2 (1.0; 4.6) times higher odds of MAP infection compared to those in flocks alternating anti-parasitic compounds. These results should be considered in the development of a nationwide future control program fοr caprine paratuberculosis in Greece., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Bayesian mixture models can be used to discriminate between the distributions of continuous test responses for different infection stages. These models are particularly useful in case of chronic infections with a long latent period, like Mycobacterium avium subsp. paratuberculosis (MAP) infection, where a perfect reference test does not exist. However, their discriminatory ability diminishes with increasing overlap of the distributions and with increasing number of latent infection stages to be discriminated. We provide a method that uses partially verified data, with known infection status for some individuals, in order to minimize this loss in the discriminatory power. The distribution of the continuous antibody response against MAP has been obtained for healthy, MAP-infected and MAP-infectious cows of different age groups. The overall power of the milk-ELISA to discriminate between healthy and MAP-infected cows was extremely poor but was high between healthy and MAP-infectious. The discriminatory ability increased with increasing age. The great overlap between the distributions of the different infection stages would have hampered our ability to discriminate between the different infection stages. Thus, the proposed method, which uses partially verified data on the true status for some individuals, is an intuitive extension to the standard non-gold standard methods, especially in the case of infections with a long latent period., (Copyright © 2013. Published by Elsevier B.V.)

Survival analysis methods can be used to identify factors associated with the time to induction of infection. In the absence of a perfect test, detection of infection is generally delayed and depends on the duration of the latent infection period. We assess, via simulations, the impact of ignoring the delayed detection of infection on estimated survival times and propose a Bayesian Weibull regression model, which adjusts for the delayed detection of infection. The presence of non-differential detection delay seriously biased the baseline hazard and the shape of the hazard function. For differential detection delay, the associated regression coefficients were also biased. The extent of bias largely depended on the longevity of the delay. In all considered simulation scenarios our model led to corrected estimates. We utilized the proposed model in order to assess the age at natural infection with Mycobacterium avium subsp. paratuberculosis (MAP) in Danish dairy cattle from the analysis of available time to milk-seropositivity data that detected infection with delay. The proposed model captured the inverse relationship between the incidence rate of infection and that of seroconversion with time: susceptibility to infection decreases with time (shape parameter under the proposed model was rho=0.56<1), while older animals had a higher probability of sero-converting (rho=2.67>1, under standard Weibull regression). Cows infected earlier in their lives were more likely to subsequently shed detectable levels of MAP and, hence, be a liability to herd-mates. Our approach can be particularly useful in the case of chronic infections with a long latent infection period, which, if ignored, severely affects survival estimates., (Copyright 2010 Elsevier B.V. All rights reserved.)

The variance partition coefficient (VPC) measures the clustering of infection/disease among individuals with a specific covariate pattern. Covariate-pattern-specific VPCs provide insight to the groups of individuals that exhibit great heterogeneity and should be targeted for intervention. VPCs should be taken into consideration when planning study designs, modeling data and estimating sample sizes. We present a Bayesian discrete mixed model for the estimation of covariate-pattern-specific VPCs when measurement of the infection/disease is based on an imperfect test. The utility of the presented model is demonstrated with three applications. In all cases, imperfect tests biased VPC estimates towards the null but corrected estimates could be obtained by modeling the sensitivity and specificity of the test procedure with beta distributions. The comparison of adjusted VPCs between the intercept only and the fitted models with higher level covariates explained the portion of heterogeneity in the data that was accounted for by the covariates.

The requirements for the isolation of Mycobacterium avium subsp. paratuberculosis (Map) may be related to the strain-type [sheep (S)- or cattle (C)-type] and not to the host. The objective of this paper was to estimate and compare strain- and biological sample (faeces or pooled-tissue)--specific sensitivities (Ses) of two solid culture media, Herrold's egg yolk medium (HEYM) and Lowenstein-Jensen (LJ) medium, for the isolation of Map from Greek dairy sheep and goats. From 400 faecal samples collected from sub-clinically infected sheep and goats of four flocks and from 214 pooled-tissue samples (142 from sheep and 72 from goats) collected, at the abattoir, from >1-year-old routinely slaughtered animals, with gross pathology suggestive of paratuberculosis, we isolated 34 Map strains. Of those, by the IS1311 PCR, 18 were categorized into the C-type and nine into the S-type; seven were not typed. We used a Bayesian approach to estimate the strain-specific Ses. SeHEYM-C-faecal=17% (95% credible interval: 7, 40) was higher than SeHEYM-S-faecal=2% (0.3, 11). Also, SeHEYM-C-faecal was higher than SeLJ-C-faecal=4% (1, 12). In pooled-tissue samples, the strain-specific Ses did not differ between the two media.

Latent class models were used to estimate the sensitivity (Se) and the specificity (Sp) of a serum ELISA and a faecal culture (FC) method for the diagnosis of paratuberculosis separately, in sheep and goats. The estimates were obtained by a Bayesian method. Possible dependence of diagnostic errors was investigated by comparing models where independence was assumed to models allowing for conditional dependence given the true disease status. ROC analysis for the serum ELISA was also performed and optimized cut-off values based on the misclassification cost term were determined. No evidence of conditional dependence was found. Assuming independence, posterior medians and 95% credible intervals for the Se(ELISA), Sp(ELISA), Se(FC) and Sp(FC), were 63% (42, 93%), 95% (90, 98%), 8% (2, 17%) and 98% (95, 100%) in goats and 37% (10, 80%), 97% (93, 99%), 16% (2, 48%) and 97% (95, 99%) in sheep. AUC was calculated 0.702 for sheep and 0.847 for goats. For the serum ELISA, there is need of species- and purpose-specific cut-off selection. For instance, with 20% prevalence situation and assuming equal and five-fold cost of a false negative to a false positive test result, the optimal cut-off is 0.3 and 0.05 in sheep, respectively, while it is 0.6 and 0.1 in goats, respectively. Serum ELISA performed better in goats than in sheep. Lowering the cut-off, in relation to the one recommended by the manufacturer, improved Se(ELISA) without seriously compromising Sp(ELISA), in either species.

In this study, we compared the frequency of isolation of Mycobacterium avium subsp. paratuberculosis (MAP) from faecal samples grown on Herrold's egg-yolk medium (HEYM) or on Lowenstein-Jensen (LJ) medium and estimated the sensitivity (Se) and specificity (Sp) of the methods separately in sub-clinically infected Greek dairy sheep and goats, using latent-class models and Bayesian estimation procedures. Faecal and blood samples were collected from 400 animals > or =1 year old in April-May 2002. The HEYM supported growth of MAP better than the LJ method and their agreement was very poor (weighted kappa=0.062 (95% CI: -0.098, 0.222)). There was no evidence of dependence between the Ses whereas the Sps were positively correlated. Thus, a semi-dependent model that assumed independence of Ses and accounted for the dependence of Sps was adopted. Under this model, the parallel interpretation of the results of the two methods gave median estimates and 95% credible intervals (CrIs) for Se(par), Sp(par) of 15% (CrIs: 3, 45%), 96% (92, 98%) in sheep and 16% (6, 36%) and 97% (94, 99%) in goats.

Our cross-sectional study investigated the association of sub-clinical Mycobacterium avium subsp. paratuberculosis (MAP) infection with failing to produce a live offspring the season of lambing/kidding (November 2001 to January 2002) before testing (in April-May 2002), in four dairy-sheep and/or goat flocks in Greece (369 animals >or=1.5-year-old). From each selected animal 10 ml of blood and 10 g of feces from the rectum were obtained. The harvested sera were tested for antibodies to MAP with a commercial ELISA test kit; the feces were cultured on Herrold's egg-yolk medium supplemented with mycobactin J and antibiotics. An animal was considered sub-clinically infected when found either seropositive or culture positive. The true prevalence of sub-clinically infected animals, adjusted for the sensitivity and specificity of the parallel testing, was 14% (0.1-28%) and 35.9% (9.2-62.7%) in sheep and goats, respectively. The association of fertility of sheep and goats with sub-clinical paratuberculosis was investigated in random-effects logistic models. Sub-clinically infected animals (compared to uninfected) had OR for live offspring the previous year of 5.4 for parity <4, OR=0.05 for parity >6, and a non-significant OR for the middle parity category.

Disease cases are often clustered within herds or generally groups that share common characteristics. Sample size formulae must adjust for the within-cluster correlation of the primary sampling units. Traditionally, the intra-cluster correlation coefficient (ICC), which is an average measure of the data heterogeneity, has been used to modify formulae for individual sample size estimation. However, subgroups of animals sharing common characteristics, may exhibit excessively less or more heterogeneity. Hence, sample size estimates based on the ICC may not achieve the desired precision and power when applied to these groups. We propose the use of the variance partition coefficient (VPC), which measures the clustering of infection/disease for individuals with a common risk profile. Sample size estimates are obtained separately for those groups that exhibit markedly different heterogeneity, thus, optimizing resource allocation. A VPC-based predictive simulation method for sample size estimation to substantiate freedom from disease is presented. To illustrate the benefits of the proposed approach we give two examples with the analysis of data from a risk factor study on Mycobacterium avium subsp. paratuberculosis infection, in Danish dairy cattle and a study on critical control points for Salmonella cross-contamination of pork, in Greek slaughterhouses. [ABSTRACT FROM AUTHOR]

Abstract: We estimated the prevalence of Mycobacterium avium subsp. paratuberculosis (MAP) infected sheep and goats, older than 2 years, reared in the region effectively controlled by the Government of the Republic of Cyprus, in September 2005. The sera collected from 8011 animals (3429 sheep and 4582 goats) from 83 flocks, non-vaccinated against MAP, were examined for antibodies with a commercially available enzyme linked immunosorbent assay (Pourquier® paratuberculosis antibody screening ELISA). The true prevalence of MAP infection was calculated, in a Bayesian framework, separately in sheep and goats, with models that adjusted for the misclassification of animals because of the imperfect accuracy of the ELISA. The within-flock mean seroprevalence in sheep and goats was 9.9% (95% CI: 8.9; 10.9%) and 7.9% (7.2; 8.7%), respectively. There was at least one seropositive sheep in 52% (38; 66%) of flocks with sheep and one seropositive goat in 50% (39; 62%) of flocks with goats. Within the seropositive flocks the mean seroprevalence was 12.1% (10.9; 13.4%) and 10.3% (9.3; 11.4%) in sheep and goats, respectively. The calculated mean true prevalence of infected sheep and goats was 15.0 and 11.1%, respectively. There was at least one infected sheep in 60.8% (95% credible interval: 42.3; 78.8%) and at least an infected goat in 48.6% (30.4; 68.5%) of the flocks. In the infected flocks, the mean within flock true prevalence of infection in sheep and goats was estimated at 24.6% (16.3; 33.3%) and 23.1% (15.5; 33.6%), respectively. [Copyright &y& Elsevier]

We validated a commercial (Idexx Pourquier, Montpellier, France) serum and milk indirect ELISA that detects antibodies against Mycobacterium avium ssp. paratuberculosis (MAP) in Greek dairy goats. Each goat was sampled 4 times, starting from kidding and covering early, mid, and late lactation. A total of 1,268 paired milk (or colostrum) and serum samples were collected during the 7-mo lactation period. Bayesian latent class models, which allow for the continuous interpretation of test results, were used to derive the distribution of the serum and milk ELISA response for healthy and MAP-infected individuals at each lactation stage. Both serum and milk ELISA, in all lactation stages, had average and similar overall discriminatory ability as measured by the area under the curve (AUC). For each test, the smallest overlap between the distribution of the healthy and MAP-infected does was in late lactation. At this stage, the AUC was 0.89 (95% credible interval: 0.70; 0.98) and 0.92 (0.74; 0.99) for the milk and serum ELISA, respectively. Both tests had comparable sensitivities and specificities at the recommended cutoffs across lactation. Lowering the cutoffs led to an increase in sensitivity without serious loss in specificity. In conclusion, the milk ELISA was as accurate as the serum ELISA. Therefore, it could serve as the diagnostic tool of choice, especially during the implementation of MAP control programs that require frequent testing, because milk sampling is a noninvasive, rapid, and easy process. [ABSTRACT FROM AUTHOR]