Evaluation of a multiplex assay and two commercial ELISAs for the serological detection of Actinobacillus pleuropneumoniae using Bayesian latent class modelling

Abstract Actinobacillus pleuropneumoniae (APP) remains a major cause of respiratory disease in swine and accurate serological tools are essential for surveillance, particularly in sub-clinical herds and low prevalence settings. We evaluated the diagnostic performance of a microsphere-based multiplex fluorescent immunoassay (MFIA) and two commercial ELISAs (1–12 ELISA and ApxIV ELISA) using a Bayesian latent class model and field samples from Norwegian swine herds. Although both ELISAs and the MFIA showed high specificity, the ApxIV ELISA demonstrated lower sensitivity (89.4%) than the other assays. These findings align with previously reported variability in the sensitivity of the ApxIV-based ELISA. The MFIA showed high sensitivity, demonstrating the potential of multiplex immunoassays for APP serology. We also explored optimization of the ApxIV ELISA cut-off, which indicated that lowering the threshold could improve the sensitivity of the test without compromising the specificity for our samples. Our estimates can be influenced by several factors, including the serotype diversity in the population and assumptions related to latent class modelling. Despite these constraints, our findings support the use of MFIA and the ELISAs as accurate tools for APP surveillance, while highlighting that the ApxIV ELISA may be less suitable as a stand-alone screening test. These results underscore the importance of validating diagnostic assays in populations where they will be applied to ensure that they are fit-for-purpose.