...
首页> 外文期刊>Veterinary research >Modelling of paratuberculosis spread between dairy cattle farms at a regional scale
【24h】

Modelling of paratuberculosis spread between dairy cattle farms at a regional scale

机译:在区域规模的奶牛场之间传播的副结核病模型

获取原文
   

获取外文期刊封面封底 >>

       

摘要

Mycobacterium avium subsp. paratuberculosis (Map) causes Johne’s disease, with large economic consequences for dairy cattle producers worldwide. Map spread between farms is mainly due to animal movements. Locally, herd size and management are expected to influence infection dynamics. To provide a better understanding of Map spread between dairy cattle farms at a regional scale, we describe the first spatio-temporal model accounting simultaneously for population and infection dynamics and indirect local transmission within dairy farms, and between-farm transmission through animal trade. This model is applied to Brittany, a French region characterized by a high density of dairy cattle, based on data on animal trade, herd size and farm management (birth, death, renewal, and culling) from 2005 to 2013 for 12 857 dairy farms. In all simulated scenarios, Map infection highly persisted at the metapopulation scale. The characteristics of initially infected farms strongly impacted the regional Map spread. Network-related features of incident farms influenced their ability to contaminate disease-free farms. At the herd level, we highlighted a balanced effect of the number of animals purchased: when large, it led to a high probability of farm infection but to a low persistence. This effect was reduced when prevalence in initially infected farms increased. Implications of our findings in the current enzootic situation are that the risk of infection quickly becomes high for farms buying more than three animals per year. Even in regions with a low proportion of infected farms, Map spread will not fade out spontaneously without the use of effective control strategies.
机译:鸟分枝杆菌亚种副结核病(地图)引起约翰内氏病,对全世界的奶牛生产者造成巨大的经济影响。农场之间分布的地图主要是由于动物的移动。在当地,预计牛群的大小和管理会影响感染的动态。为了更好地了解区域范围内奶牛场之间的地图传播,我们描述了第一个时空模型,该模型同时考虑了人口和感染动态以及奶牛场内的间接局部传播,以及通过动物贸易的农场间传播。基于2005年至2013年间12 857个奶牛场的动物贸易,畜群规模和农场管理(出生,死亡,更新和淘汰)数据,该模型已应用于布列塔尼地区,该地区以奶牛高密度为特征。在所有模拟情况下,Map感染在种群规模上都高度持久。最初受感染的农场的特征极大地影响了该地区的地图传播。事件农场的网络相关特征影响了它们污染无病农场的能力。在畜群一级,我们强调了所购动物数量的均衡影响:大牲畜导致农场感染的可能性很高,但持久性却很低。当最初感染的农场中的流行率增加时,这种影响就会减弱。在当前的动物疫情中,我们的发现意味着对于每年购买三只以上动物的农场,感染的风险迅速升高。即使在受感染农场比例较低的地区,如果不使用有效的控制策略,地图的传播也不会自发消失。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号