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Continuous-Data Diagnostic Tests for Paratuberculosis as a Multistage Disease

¹ Department of Large Animal Sciences, The Royal Veterinary and Agricultural University, Grønnegårdsvej 8, DK-1870 Frederiksberg C, Denmark
² Biometry Research Unit, Danish Institute of Agricultural Sciences, P.O. Box 50, DK-8830, Tjele, Denmark

Corresponding author: Nils Toft; e-mail: nt{at}dina.kvl.dk.

We devised a general method for interpretation of multistage diseases using continuous-data diagnostic tests. As an example, we used paratuberculosis as a multistage infection with 2 stages of infection as well as a noninfected state. Using data from a Danish research project, a fecal culture testing scheme was linked to an indirect ELISA and adjusted for covariates (parity, age at first calving, and days in milk). We used the log-transformed optical densities in a Bayesian network to obtain the probabilities for each of the 3 infection stages for a given optical density (adjusted for covariates). The strength of this approach was that the uncertainty associated with a test was imposed directly on the individual test result rather than aggregated into the population-based measures of test properties (i.e., sensitivity and specificity).

Key Words: paratuberculosis • ELISA • Bayesian network • test evaluation

Abbreviation key: FC = fecal culture, FC_high = fecal culture high, FC_low = fecal culture low, FC_neg = fecal culture negative, Map = Mycobacterium avium ssp. paratuberculosis, OD = optical density, Pr = probability.

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