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

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.

早期精准诊断是梅迪-维斯纳病毒（maedi-visna virus, MVV）成功开展监测与防控的核心基础。本研究旨在评估三款商用酶联免疫吸附试验（Enzyme-Linked Immunosorbent Assay, ELISA）试剂盒对MVV抗体的检测性能。我们针对2019年挪威6个确诊感染MVV的羊场采集的615份样本开展回顾性研究，使用以下三款试剂盒对所有样本进行检测：ID Screen® MVV/CAEV间接法试剂盒（IDvet公司，法国格拉贝尔）、IDEXX MVV/CAEV p28抗体验证试剂盒（IDEXX实验室，美国缅因州）以及Elitest MVV/CAEV试剂盒（Hyphen Biomed公司，法国瓦兹河畔讷维尔）。由于缺乏完美的金标准参考检测方法，我们采用贝叶斯隐类别分析（Bayesian latent class analysis），纳入检测间的条件依赖关系，以估算各羊场的诊断准确度与真实感染患病率。本数据集包含所有样本的检测结果及其所属羊场信息。配套的R脚本文件包含本次贝叶斯隐类别分析所使用的模型代码。