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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/20908

Title: Serological diagnosis of bovine neosporosis: a Bayesian evaluation of two Antibody ELISA tests for in vivo diagnosis in purchased an abortion cattle.
Authors: Roelandt, S.
Van der Stede, Y.
Czaplicki, G.
Van Loo, H.
Van Driessche, E.
Dewulf, J.
Hooyberghs, J.
Faes, C.
Issue Date: 2015
Citation: Veterinary record 176(23)
Abstract: Currently, there are no perfect reference tests for the in vivo detection of Neospora caninum infection. Two commercial N caninum ELISA tests are currently used in Belgium for bovine sera (TEST A and TEST B). The goal of this study is to evaluate these tests used at their current cut-offs, with a no gold standard approach, for the test purpose of (1) demonstration of freedom of infection at purchase and (2) diagnosis in aborting cattle. Sera of two study populations, Abortion population (n=196) and Purchase population (n=514), were selected and tested with both ELISA's. Test results were entered in a Bayesian model with informative priors on population prevalences only (Scenario 1). As sensitivity analysis, two more models were used: one with informative priors on test diagnostic accuracy (Scenario 2) and one with all priors uninformative (Scenario 3). The accuracy parameters were estimated from the first model: diagnostic sensitivity (Test A: 93.54 per cent–Test B: 86.99 per cent) and specificity (Test A: 90.22 per cent–Test B: 90.15 per cent) were high and comparable (Bayesian P values >0.05). Based on predictive values in the two study populations, both tests were fit for purpose, despite an expected false negative fraction of ±0.5 per cent in the Purchase population and ±5 per cent in the Abortion population. In addition, a false positive fraction of ±3 per cent in the overall Purchase population and ±4 per cent in the overall Abortion population was found.
URI: http://hdl.handle.net/1942/20908
DOI: 10.1136/vr.102872
ISI #: 000356167400018
ISSN: 0042-4900
Category: A1
Type: Journal Contribution
Validation: ecoom, 2016
Appears in Collections: Research publications

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