一个新的贝叶斯隐藏类模型 (BLCM) 评估了多个连续和二进制测试:乳牛中Brucella abortus的案例研究
Yu Wang1, Emilie Vallée1, Chris Compton1
1EpiCentre, School of Veterinary Science - Tāwharau Ora, Massey University, Palmerston North, New Zealand.
Preventive veterinary medicine
|January 14, 2024
概括
一个新的贝叶斯模型精确校准了在中国的牛肉病的诊断测试. 这有助于改善乳制品农场中Brucella abortus的疾病检测和控制策略.
科学领域:
- 兽医流行病学 兽医流行病学
- 诊断测试评价 诊断测试评价
- 贝叶斯统计学贝叶斯统计学
背景情况:
- 牛牛病是由Brucella abortus引起的,对动物和人类健康构成重大风险.
- 准确的诊断对于有效的控制和预防策略至关重要.
- 缺少黄金标准测试使诊断测试性能评估和切断值确定复杂化.
研究的目的:
- 开发和应用一个新的贝叶斯潜伏类模型,用于校准诊断测试的最佳切断值.
- 为了评估四个牛肉血清学测试的诊断性能,用于牛肉血清病.
- 估计真正的疾病患病率,并确定中国奶牛场的风险因素.
主要方法:
- 开发了一个贝叶斯隐性类模型,将二进制和连续测试结果与固定 (平价) 和随机 (农场) 效应集成在一起.
- 来自中国河南省六个奶牛农场的651个血清样本使用孟加拉试验,血清凝结试验,光极化试验和竞争性酶链接免疫吸收试验进行了测试.
- 通过最大化Youden指数来确定最佳切断值.
主要成果:
- 确定了最佳切断值为光极化试验的94.2mP和竞争性酶相关免疫吸收试验的0.403PI.
- 测试灵敏度在69.7%至89.9%之间,特异性在97.1%至99.6%之间.
- 两个研究区域的真实患病率分别为4.7%和30.3%,平价影响血清状况 (ORs 1.22.2).
结论:
- 开发的贝叶斯模型为在没有黄金标准的情况下验证诊断测试提供了一个强大的框架.
- 这些发现为牛牛菌病监测中使用的关键血清学测试提供了优化的切断值和性能估计.
- 这项研究支持在中国乳制品种群中设计有针对性的检测策略和有效的乳病控制措施.
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