使用专家诱导,将埃塞俄比亚的动物健康损失归因于高层原因
Andrew Larkins1, Wudu Temesgen2, Gemma Chaters3
1School of Veterinary Medicine, Harry Butler Institute, Murdoch University, 90 South Street, Murdoch, Western Australia 6150, Australia.
Preventive veterinary medicine
|November 17, 2023
概括
在埃塞俄比亚,传染病造成的动物健康损失至少占40%. 这项研究使用了结构化的专家诱导来快速归因动物疾病负担.
科学领域:
- 兽医流行病学 兽医流行病学
- 动物健康经济学 动物健康经济学
- 畜牧业生产 畜牧业生产
背景情况:
- 估计动物疾病负担对于埃塞俄比亚有效的畜牧管理和经济稳定至关重要.
- 全球动物疾病负担计划旨在量化埃塞俄比亚的动物健康损失.
- 将健康损失归因于特定原因是复杂的,但对于有针对性的干预来说至关重要.
研究的目的:
- 试验结构化的专家诱导,以将动物健康损失比例归因于高级原因 (传染性,非传染性,外部).
- 估计埃塞俄比亚牲畜中因传染性,非传染性和外部原因造成的动物健康损失的比例.
- 评估一种快速,引人入胜的方法对高级负担分配的有用性.
主要方法:
- 使用调查-讨论-估计-汇总协议进行结构化的专家提取.
- 与8名牛,9名小反动物和8名专家进行了面对面的研讨会.
- 三点问题为β-pert分布提供信息并捕捉不确定性;以量子平均值汇总.
主要成果:
- 据估计,感染病因在埃塞俄比亚所有牲畜类别中造成的健康损失比例最高.
- 至少40%的总动物健康损失是由于传染病引起的.
- 根据物种,年龄性别等级和生产系统,估计数量各不相同,这凸显了需要详细分析的必要性.
结论:
- 结构化专家提取提供了一种快速,简单和有吸引力的方法,用于对动物健康损失的高级别归因.
- 传染病对埃塞俄比亚的牲畜来说是一个很大的负担.
- 结果提供了有价值的基线数据,可以通过未来的数据驱动建模来增强.
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