Vigre Håkan, Dohoo Ian R, Stryhn Henrik, Busch Marie Erika
Danish Institute for Food and Veterinary Research, Copenhagen V, Denmark.
Prev Vet Med. 2004 Apr 30;63(1-2):9-28. doi: 10.1016/j.prevetmed.2004.02.002.
In this paper, multilevel logistic models which take into account the multilevel structure of multi-site pig production were used to estimate the variances between pigs produced in Danish multi-site pig production facilities regarding seroconversion to Actinobacillus pleuropneumoniae serotype 2 (Ap2) and Mycoplasma hyopneumoniae (Mh). Based on the estimated variances, three newly described computational methods (model linearisation, simulation and linear modelling) and the standard method (latent-variable approach) were used to estimate the correlations (intra-class correlation components, ICCs) between pigs in the same production unit regarding seroconversion. Substantially different values of ICCs were obtained from the four methods. However, ICCs obtained by the simulation and the model linearisation were quite consistent. Data used for estimation were collected from 1161 pigs from 429 litters reared in 36 batches at six Danish multi-site farms chronically infected with the agents. At the farms, weaning age was 3-4.5 weeks, after which batches of pigs were reared using all-in/all-out management by room. Blood samples were collected shortly before: weaning, transfer from weaning-site to finishing-site, and sending the first pigs in the batch for slaughter (third sampling). Few pigs seroconverted at the weaning-sites, whereas considerable variation in seroconversion was observed at the finishing-sites. Multilevel logistic models (initially including four levels: farm, batch, litter, pig) were used to decompose the variation in seroconversion at the finishing-site. However, there was essentially no clustering at the litter level-leading to the use of three-level models. In the case of Ap2, clustering within batch was so high that the data eventually were reduced to two levels (farm, batch). For seroconversion to Ap2, ICC between pigs within batches was approximately 90%, whereas the ICC between pigs within batches for Mh was approximately 40%. This indicates that the possibility for Mh to spread between pigs within batches is lower than for Ap2. The diversity in seroconversion between batches within the same farm was large for Ap2 (ICC approximately 10%), whereas there was a relative strongly ICC (approximately 50%) between batches for Mh. This indicates that the transmission of Mh is more consistent within a farm, whereas the presence of Ap2 varies between batches within a farm.
在本文中,采用考虑了多地点生猪生产多级结构的多级逻辑模型,来估计丹麦多地点生猪生产设施中生产的猪只之间,针对胸膜肺炎放线杆菌2型(Ap2)和猪肺炎支原体(Mh)血清转化的方差。基于估计的方差,使用三种新描述的计算方法(模型线性化、模拟和线性建模)以及标准方法(潜在变量方法),来估计同一生产单元内猪只之间关于血清转化的相关性(类内相关成分,ICCs)。从这四种方法获得的ICCs值存在很大差异。然而,通过模拟和模型线性化获得的ICCs相当一致。用于估计的数据收集自丹麦六个长期感染病原体的多地点农场中36批次饲养的429窝1161头猪。在这些农场,断奶年龄为3至4.5周,之后按批次整进整出的方式在猪舍饲养猪只。在断奶前、从断奶地点转移到育肥地点以及将批次中的第一批猪送去屠宰(第三次采样)前不久采集血样。在断奶地点很少有猪发生血清转化,而在育肥地点观察到血清转化存在相当大的差异。多级逻辑模型(最初包括四个层次:农场、批次、窝、猪)用于分解育肥地点血清转化的变异。然而,在窝水平上基本没有聚类现象,因此最终使用了三级模型。对于Ap2,批次内的聚类程度很高,以至于数据最终简化为两个层次(农场、批次)。对于Ap2血清转化,批次内猪只之间的ICC约为90%,而对于Mh,批次内猪只之间的ICC约为40%。这表明Mh在批次内猪只之间传播的可能性低于Ap2。对于Ap2,同一农场内批次之间血清转化的多样性很大(ICC约为10%),而对于Mh,批次之间存在相对较强的ICC(约为50%)。这表明Mh在一个农场内的传播更一致,而Ap2在一个农场内的不同批次之间存在差异。