Supplementary information for: "Evaluation of three commercial ELISA tests for serological detection of maedi-visna virus using Bayesian latent class analysis"

Dataset

DOI

Early and accurate diagnosis is fundamental for successful surveillance and control of maedi-visna virus (MVV). Our study aimed to evaluate three commercial ELISA tests for MVV antibodies. We conducted a retrospective study using 615 samples from six flocks diagnosed with MVV in Norway in 2019. We ran all samples with the following three tests: ID Screen® MVV/CAEV Indirect kit (IDvet, Grabels, France), IDEXX MVV/CAEV p28 Ab Verification Test (IDEXX Laboratories, Maine, USA) and Elitest MVV/CAEV (Hyphen Biomed, Neuville-sur-Oise, France). 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. The dataset contains the test results of all samples and which flock they are from. The Rscript contains the model used for the Bayesian latent class analysis.

R, Version 4.2.1

Identifier
DOI	https://doi.org/10.18710/LSQ4ES
Related Identifier	https://doi.org/10.1016/j.prevetmed.2022.105765
Metadata Access	https://dataverse.no/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18710/LSQ4ES

Provenance
Creator	Jerre, Anniken
Publisher	DataverseNO
Contributor	Jerre, Anniken; Norwegian University of Life Sciences; Nordstoga, Anne B.; Holmøy, Ingrid H.; Dean, Katharine R.; NMBU Open Research Data
Publication Year	2022
Funding Reference	The Norwegian Research Fund for Agriculture and Food Industry, 310753; Animalia Norwegian Meat and Poultry Research Centre
Rights	CC0 1.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess	true
Contact	Jerre, Anniken

Representation
Resource Type	Experimental data; Dataset
Format	text/plain; text/csv; type/x-r-syntax
Size	3996; 11541; 5884
Version	1.1
Discipline	Life Sciences; Medicine