Martin P A J, Cameron A R, Barfod K, Sergeant E S G, Greiner M
Department of Agriculture and Food, PO Box 1231, Bunbury, Western Australia 6231, Australia.
Prev Vet Med. 2007 May 16;79(2-4):98-115. doi: 10.1016/j.prevetmed.2006.09.007. Epub 2007 Jan 18.
A method for quantitative evaluation of surveillance for disease freedom has been presented in the accompanying paper (Martin et al., 2007). This paper presents an application of the methods, using as an example surveillance for classical swine fever (CSF) in Denmark in 2005. A scenario tree model is presented for the abattoir-based serology component of the Danish CSF surveillance system, in which blood samples are collected in an ad hoc abattoir sampling process, from adult pigs originating in breeding herds in Denmark. The model incorporates effects of targeting (differential risk of seropositivity) associated with age and location (county), and disease clustering within herds. A surveillance time period of one month was used in the analysis. Records for the year 2005 were analysed, representing 25,332 samples from 3528 herds; all were negative for CSF-specific antibodies. Design prevalences of 0.1-1% of herds and 5% of animals within an infected herd were used. The estimated mean surveillance system component (SSC) sensitivities (probability that the SSC would give a positive outcome given the animals processed and that the country is infected at the design prevalences) per month were 0.18, 0.63 and 0.86, for among-herd design prevalences of 0.001, 0.005 and 0.01. The probabilities that the population was free from CSF at each of these design prevalences, after a year of accumulated negative surveillance data, were 0.91, 1.00 and 1.00. Targeting adults and herds from South Jutland was estimated to give approximately 1.9, 1.6 and 1.4 times the surveillance sensitivity of a proportionally representative sampling program for these three among-herd design prevalences.
随附论文（Martin等人，2007年）中提出了一种对无病监测进行定量评估的方法。本文介绍了该方法的应用，以2005年丹麦对经典猪瘟（CSF）的监测为例。针对丹麦CSF监测系统中基于屠宰场的血清学部分，提出了一个情景树模型，在该模型中，血液样本是在临时的屠宰场采样过程中从丹麦种猪群的成年猪中采集的。该模型纳入了与年龄和地点（县）相关的靶向效应（血清阳性的差异风险）以及猪群内的疾病聚集情况。分析中使用了一个月的监测时间段。对2005年的记录进行了分析，代表来自3528个猪群的25332个样本；所有样本的CSF特异性抗体均为阴性。使用了感染猪群中0.1 - 1%的猪群和5%的动物的设计患病率。对于猪群间设计患病率分别为0.001、0.005和0.01的情况，每月估计的平均监测系统组件（SSC）敏感性（在给定处理的动物且国家在设计患病率下被感染的情况下，SSC得出阳性结果的概率）分别为0.18、0.63和0.86。在积累了一年的阴性监测数据后，在这些设计患病率下，种群无CSF的概率分别为0.91、1.00和1.00。对于这三种猪群间设计患病率，估计针对日德兰半岛南部的成年猪和猪群进行采样，其监测敏感性约为按比例代表性采样方案的1.9、1.6和1.4倍。
