RESUMO
To quantify the sensitivity and specificity of a serum enzyme-linked immunosorbent assay (ELISA) and fecal culture (FC) tests and to estimate the prevalence of Johne's disease (JD) in New Zealand dairy herds using Bayesian methods, 4 New Zealand dairy herds were tested simultaneously by ELISA and FC 5 times over 3 lactations. Test results were dichotomized. A Bayesian regression model was developed that considered test sensitivity as a function of the covariates parity, lactation stage, and prevalence of JD, which is expected to vary between herds. It was applied to a cross-sectional subset of the data and the full, repeated measures data set. Results were compared with frequentist pseudo gold standard results of the full data. Using the regression model, sensitivity of the ELISA was higher in older animals, but the sensitivity of the FC test showed no trend across age groups. Both FC and ELISA sensitivity were lower in late lactation. Estimated prevalence was lower and FC sensitivity higher when analyzing the complete data. The regression model enabled a more accurate diagnosis of JD to be made because it incorporated cow-specific information in the diagnosis, such as age and lactation stage. The model also enabled the incorporation of previous test results for an individual when diagnosing disease. The trends in results from the regression model support the current understanding of the disease process. The advantage of repeated testing of individuals in the assessment of test performance is discussed in the current study.