将动态通用线性模型和机械模型结合起来,以优化针对牛呼吸道疾病的治疗策略
Carolina Merca1, Baptiste Sorin-Dupont2, Anders Ringgaard Kristensen3
1Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 2, 1870, Frederiksberg C, Denmark. cmgm@sund.ku.dk.
Veterinary research
|September 26, 2025
概括
一个新的决策支持工具帮助农民管理年轻公牛的牛呼吸道疾病 (BRD). 它优化了集体治疗时间,减少了疾病的影响和抗菌素使用 (AMU).
科学领域:
- 兽医医学 兽医医学 兽医医学
- 动物健康管理 动物健康管理
- 流行病学 流行病学
背景情况:
- 牛呼吸道疾病 (BRD) 在年轻公牛中带来了重大经济挑战.
- 目前对BRD的集体治疗策略涉及疾病控制和抗菌素使用 (AMU) 之间的妥协.
- 关于集体治疗时间的知情决策对于优化动物福利和资源管理至关重要.
研究的目的:
- 引入一个概念验证决策支持工具,以优化牛群集体BRD治疗时间.
- 整合一个模拟引擎和一个动态通用线性模型 (DGLM) 进行早期预警感染风险估计.
- 评估该工具对各种农场场景的BRD发病率,严重程度和AMU的影响.
主要方法:
- 开发了一个框架,将BRD传播 (Mannheimia haemolytica) 的机械静态模拟引擎和一个层次的多变量二项式DGLM结合起来.
- 模拟了48种不同批量大小,农场风险水平,批量分配和治疗干预 (个人,传统集体,基于DGLM的集体) 的场景.
- 评估基于DGLM的早期警告与经验风险估计,并评估治疗结果.
主要成果:
- 由DGLM触发的集体治疗在高和中风险情景中降低了BRD累积发病率和严重程度,特别是在大群体中.
- 与传统方法相比,基于DGLM的集体治疗通常导致抗菌剂使用量 (AMU) 较低或相当,在中等,平衡和高风险环境中显著减少.
- 在模拟的早期,DGLM感染风险估计与经验风险估计保持良好一致.
结论:
- 拟议的决策支持工具显示了指导农民和兽医在做出明智的BRD集体治疗决定的潜力.
- 该工具可以有助于改善动物福利和在畜牧业中优化抗菌剂的使用.
- 建议对现实世界,农场数据进行进一步验证,以确认该工具的有效性.
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