Bayesian estimation of sensitivity and specificity of serum ELISA and faecal culture for diagnosis of paratuberculosis in Greek dairy sheep and goats

Kostoulas, Polychronis; Leontides, Leonidas; Enøe, Claes; Billinis, C.; Florou, M.; Sofia, Marina

doi:10.1016/j.prevetmed.2006.04.006

Cited by 46 publications

(50 citation statements)

References 56 publications

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“…All models were compared using the DIC and posterior predictive p-values. To be considered significantly different, the reduction in DIC between any two models should be more than 3 units (Spiegelhalter et al, 2002;Kostoulas et al, 2006;Nérette et al, 2008). In situations where the difference in DIC was smaller than 3 units, the models were assumed to be similar and selection was based on parsimony (the smaller the number of effective parameters estimated (pD) the better) (Spiegelhalter et al, 2002).…”

Section: Modeling Conditional Dependencementioning

confidence: 99%

“…The influence of the prior information on the estimates of the diagnostic test characteristics were verified using sensitivity analysis (Branscum et al, 2005;Kostoulas et al, 2006;Praud et al, 2012). This was done by using standard uniform priors and slight perturbations (in steps of 10% or 15%) of the prior intervals (Haley et al, 2011).…”

Section: Sensitivity Analyses Of Selected Modelsmentioning

confidence: 99%

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Bayesian estimation of true prevalence, sensitivity and specificity of indirect ELISA, Rose Bengal Test and Slow Agglutination Test for the diagnosis of brucellosis in sheep and goats in Bangladesh

Rahman¹,

Saegerman²,

Berkvens³

et al. 2013

Preventive Veterinary Medicine

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a b s t r a c tThe true prevalence of brucellosis and diagnostic test characteristics of three conditionally dependent serological tests were estimated using the Bayesian approach in goats and sheep populations of Bangladesh. Serum samples from a random selection of 636 goats and 1044 sheep were tested in parallel by indirect ELISA (iELISA), Rose Bengal Test (RBT) and Slow Agglutination Test (SAT). The true prevalence of brucellosis in goats and sheep were estimated as 1% (95% credibility interval (CrI): 0.7-1.8) and 1.2% (95% CrI: 0.6-2.2) respectively. The sensitivity of iELISA was 92.9% in goats and 92.0% in sheep with corresponding specificities of 96.5% and 99.5% respectively. The sensitivity and specificity estimates of RBT were 80.2% and 99.6% in goats and 82.8% and 98.3% in sheep. The sensitivity and specificity of SAT were 57.1% and 99.3% in goats and 72.0% and 98.6% in sheep. In this study, three conditionally dependent serological tests for the diagnosis of small ruminant brucellosis in Bangladesh were validated. Considerable conditional dependence between IELISA and RBT and between RBT and SAT was observed among sheep. The influence of the priors on the model fit and estimated parameter values was checked using sensitivity analysis. In multiple test validation, conditional dependence should not be ignored when the tests are in fact conditionally dependent.

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Section: Modeling Conditional Dependencementioning

confidence: 99%

Section: Sensitivity Analyses Of Selected Modelsmentioning

confidence: 99%

Bayesian estimation of true prevalence, sensitivity and specificity of indirect ELISA, Rose Bengal Test and Slow Agglutination Test for the diagnosis of brucellosis in sheep and goats in Bangladesh

Rahman¹,

Saegerman²,

Berkvens³

et al. 2013

Preventive Veterinary Medicine

View full text Add to dashboard Cite

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“…16 Confirmation of a negative sample requires between 16-30 weeks incubation while pinpoint colonies occasionally may be visible at 12 weeks. 17 This lengthy doubling time can also allow the spread of the disease throughout domestic herds while infected cattle await diagnosis. In severe cases, the clinically infected animal may be culled before the test results have been received.…”

mentioning

confidence: 99%

“…In cattle, the sensitivity ranges from 20-73% while in sheep and goats it is much lower at 6-7%. [17][18][19] The culture technique is also hindered by the variability of bacterial growth requirements. Although it is widely known that MAP requires the use of mycobactin J for in vitro growth, several MAP field isolates have been found to be mycobactin J independent yielding a false-negative result.…”

mentioning

confidence: 99%

“…22 Specificity for the MAP ELISA ranges between 93-98% for all tested species. 17,18,23 Reports of variability in the sensitivity of the ELISA for the diagnosis of MAP-positive sera for isolates derived from different host species is not surprising since antigen preparation is not standardized. [24][25][26] Although the current challenges discussed here have been plaguing Johne disease researchers for some time, recent events in research conducted by Click et al [26][27][28][29] shed a sense of optimism on a somewhat overwhelming subject.…”

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confidence: 99%

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The Johne paradigm: From detection to management to treatment

O'Shea

2011

Virulence

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Bayesian sample size for diagnostic test studies in the absence of a gold standard: Comparing identifiable with non‐identifiable models

Dendukuri

Bélisle

Joseph

2010

Statistics in Medicine

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Diagnostic tests rarely provide perfect results. The misclassification induced by imperfect sensitivities and specificities of diagnostic tests must be accounted for when planning prevalence studies or investigations into properties of new tests. The previous work has shown that applying a single imperfect test to estimate prevalence can often result in very large sample size requirements, and that sometimes even an infinite sample size is insufficient for precise estimation because the problem is non-identifiable. Adding a second test can sometimes reduce the sample size substantially, but infinite sample sizes can still occur as the problem remains non-identifiable. We investigate the further improvement possible when three diagnostic tests are to be applied. We first develop methods required for studies when three conditionally independent tests are available, using different Bayesian criteria. We then apply these criteria to prototypic scenarios, showing that large sample size reductions can occur compared to when only one or two tests are used. As the problem is now identifiable, infinite sample sizes cannot occur except in pathological situations. Finally, we relax the conditional independence assumption, demonstrating in this once again non-identifiable situation that sample sizes may substantially grow and possibly be infinite. We apply our methods to the planning of two infectious disease studies, the first designed to estimate the prevalence of Strongyloides infection, and the second relating to estimating the sensitivity of a new test for tuberculosis transmission. The much smaller sample sizes that are typically required when three as compared to one or two tests are used should encourage researchers to plan their studies using more than two diagnostic tests whenever possible. User-friendly software is available for both design and analysis stages greatly facilitating the use of these methods.

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Bayesian estimation of sensitivity and specificity of serum ELISA and faecal culture for diagnosis of paratuberculosis in Greek dairy sheep and goats

Cited by 46 publications

References 56 publications

Bayesian estimation of true prevalence, sensitivity and specificity of indirect ELISA, Rose Bengal Test and Slow Agglutination Test for the diagnosis of brucellosis in sheep and goats in Bangladesh

Bayesian estimation of true prevalence, sensitivity and specificity of indirect ELISA, Rose Bengal Test and Slow Agglutination Test for the diagnosis of brucellosis in sheep and goats in Bangladesh

The Johne paradigm: From detection to management to treatment

Bayesian sample size for diagnostic test studies in the absence of a gold standard: Comparing identifiable with non‐identifiable models

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