Evaluation of three commercial ELISA tests for serological detection of maedi-visna virus using Bayesian latent class...

Early and accurate diagnosis is fundamental for successful surveillance and control of maedi-visna virus (MVV). MVV was detected in Norway in 2019, almost 14 years after the previous outbreak. Genetic analysis indicates persistence of the virus in the sheep population since 2005. The virus was not detected despite continuous serological surveillance. This emphasises the need for improved surveillance, which relies on an understanding of both diagnostic test performance, sampling strategy and the prevalence of the disease. This study therefore aims to evaluate three commercial ELISA tests for MVV antibodies. We conducted a retrospective study using 615 samples from six flocks diagnosed with MVV in 2019. We ran all samples with the following three tests: ID Screen® MVV/CAEV Indirect (IDvet, Grabels, France), IDEXX MVV/CAEV p28 Ab Verification Test (IDEXX Laboratories, Maine, USA) and Elitest MVV/CAEV (Hyphen Biomed, Neuville-sur-Oise, France), hereinafter referred to as ID Screen, IDEXXp28 and Elitest respectively. Without a perfect reference test, we used Bayesian latent class analysis, including conditional dependence between tests, to estimate diagnostic accuracy and true prevalence in the flocks. Using recommended cut-off values, we found that ID Screen and Elitest had significantly higher sensitivity (Se) estimates (99.3 % [97.4-100.0, 95 % Posterior Credible Interval] and 97.4 % [94.1-99.7 %], respectively) than IDEXXp28 (79.5 % [72.3-86.0 %]), while IDEXXp28 and ID Screen had significantly higher specificity (Sp) estimates than Elitest (99.7 % [99.1-100.0], 99.1 % [98.0-99.8 %] and 93.7 % [91.4-95.7 %], respectively). The estimated true prevalence in the six flocks ranged from a median of 0.8-93.5 %. Combining ID Screen and Elitest in serial interpretation showed the highest median Se and Sp (96.7 % [92.0-99.1] and 100.0 % [99.9-100.0], respectively), as well as the highest median positive predictive value (PPV) for the population with the lowest prevalence. Our study supports the use of ID Screen for screening. Further verification with Elitest in serial interpretation will enhance the PPV.