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

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.