Abstract：
Bovine brucellosis, primarily caused by Brucella abortus, severely affects both animal health and human well-being. Accurate diagnosis is crucial for designing informed control and prevention measures. Lacking a gold standard test makes it challenging to determine optimal cut-off values and evaluate the diagnostic performance of tests. In this study, we developed a novel Bayesian Latent Class Model that integrates both binary and continuous testing outcomes, incorporating additional fixed (parity) and random (farm) effects, to calibrate optimal cut-off values by maximizing Youden Index. We tested 651 serum samples collected from six dairy farms in two regions of Henan Province, China with four serological tests: Rose Bengal Test, Serum Agglutination Test, Fluorescence Polarization Assay, and Competitive Enzyme-Linked Immunosorbent Assay. Our analysis revealed that the optimal cut-off values for FPA and C-ELISA were 94.2 mP and 0.403 PI, respectively. Sensitivity estimates for the four tests ranged from 69.7% to 89.9%, while specificity estimates varied between 97.1% and 99.6%. The true prevalences in the two study regions in Henan province were 4.7% and 30.3%. Parity-specific odds ratios for positive serological status ranged from 1.2 to 2.2 for different parity groups compared to primiparous cows. This approach provides a robust framework for validating diagnostic tests for both continuous and discrete tests in the absence of a gold standard test. Our findings can enhance our ability to design targeted disease detection strategies and implement effective control measures for brucellosis in Chinese dairy farms.
摘要：
牛布鲁氏菌病,主要由流产布鲁氏菌引起,严重影响动物健康和人类福祉。准确的诊断对于设计知情的控制和预防措施至关重要。缺乏黄金标准测试使得确定最佳截止值和评估测试的诊断性能具有挑战性。在这项研究中,我们开发了一种新颖的贝叶斯潜类模型，该模型集成了二进制和连续测试结果，结合额外的固定(平价)和随机(农场)效应，通过最大化Youden指数来校准最佳临界值。我们检测了河南省两个地区6个奶牛场的651份血清样本,中国有四项血清学试验：玫瑰红试验，血清凝集试验,荧光偏振测定,和竞争性酶联免疫吸附测定。我们的分析表明，FPA和C-ELISA的最佳临界值为94.2mP和0.403PI，分别。四项测试的敏感度估计为69.7%至89.9%,而特异性估计值在97.1%和99.6%之间变化。河南省两个研究区域的真实患病率分别为4.7%和30.3%。与初产母牛相比，不同胎次组的阳性血清学状态的亲缘比在1.2至2.2之间。这种方法提供了一个强大的框架，用于在没有黄金标准测试的情况下验证连续和离散测试的诊断测试。我们的研究结果可以提高我们设计有针对性的疾病检测策略和实施有效控制中国奶牛场布鲁氏菌病的能力。
