Bayesian latent class estimation of sensitivity and specificity parameters of the PMS-PCR test for the diagnosis of cattle sub-clinically infected with Mycobacterium avium subsp. paratuberculosis
Abstract
The objective of this study was to estimate the performance of the peptide magnetic separation PCR test (PMSPCR) for the diagnosis of Mycobacterium avium subsp. paratuberculosis (MAP) in sub-clinically infected dairy cattle. Twenty-one herds were randomly selected from a source population of 131 commercial dairy herds with a known history of MAP infection, located in the De Los Rios and De Los Lagos regions, in southern Chile. In the selected herds, all milking cows with >= 2 parities and without any clinical signs were sampled, collecting feces and blood-serum samples. The PMS-PCR test was used to analyze the fecal samples, while serum samples were analyzed using a commercial ELISA kit. A Bayesian latent class model was used to estimate the sensitivity (Se) and specificity (Sp) of the diagnostic tests.
Más información
| Título según WOS: | Bayesian latent class estimation of sensitivity and specificity parameters of the PMS-PCR test for the diagnosis of cattle sub-clinically infected with Mycobacterium avium subsp. paratuberculosis |
| Título de la Revista: | PREVENTIVE VETERINARY MEDICINE |
| Volumen: | 182 |
| Editorial: | Elsevier |
| Fecha de publicación: | 2020 |
| DOI: |
10.1016/J.PREVETMED.2020.105076 |
| Notas: | ISI |