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使用情景树模型对目标畜群进行抽样检测以证实无特定疾病。

Using scenario tree modelling for targeted herd sampling to substantiate freedom from disease.

机构信息

Veterinary Public Health Institute, Vetsuisse Faculty, University of Berne, Switzerland.

出版信息

BMC Vet Res. 2011 Aug 16;7:49. doi: 10.1186/1746-6148-7-49.

Abstract

BACKGROUND

In order to optimise the cost-effectiveness of active surveillance to substantiate freedom from disease, a new approach using targeted sampling of farms was developed and applied on the example of infectious bovine rhinotracheitis (IBR) and enzootic bovine leucosis (EBL) in Switzerland. Relevant risk factors (RF) for the introduction of IBR and EBL into Swiss cattle farms were identified and their relative risks defined based on literature review and expert opinions. A quantitative model based on the scenario tree method was subsequently used to calculate the required sample size of a targeted sampling approach (TS) for a given sensitivity. We compared the sample size with that of a stratified random sample (sRS) with regard to efficiency.

RESULTS

The required sample sizes to substantiate disease freedom were 1,241 farms for IBR and 1,750 farms for EBL to detect 0.2% herd prevalence with 99% sensitivity. Using conventional sRS, the required sample sizes were 2,259 farms for IBR and 2,243 for EBL. Considering the additional administrative expenses required for the planning of TS, the risk-based approach was still more cost-effective than a sRS (40% reduction on the full survey costs for IBR and 8% for EBL) due to the considerable reduction in sample size.

CONCLUSIONS

As the model depends on RF selected through literature review and was parameterised with values estimated by experts, it is subject to some degree of uncertainty. Nevertheless, this approach provides the veterinary authorities with a promising tool for future cost-effective sampling designs.

摘要

背景

为了优化主动监测的成本效益,以证明疾病的消除,我们开发了一种新的方法,即通过对农场进行靶向抽样,以瑞士传染性牛鼻气管炎(IBR)和牛白血病(EBL)为例进行应用。确定了引入 IBR 和 EBL 进入瑞士牛场的相关风险因素(RF),并根据文献回顾和专家意见定义了它们的相对风险。随后,我们使用基于情景树方法的定量模型来计算给定敏感性的靶向抽样方法(TS)所需的样本量。我们比较了两种方法(TS 和 sRS)的效率,以确定所需的样本量。

结果

为了证明疾病的消除,IBR 和 EBL 的目标抽样方法(TS)分别需要 1241 个和 1750 个农场,以检测 0.2%的畜群流行率,灵敏度为 99%。使用传统的分层随机抽样(sRS),IBR 和 EBL 的所需样本量分别为 2259 个和 2243 个。考虑到 TS 规划所需的额外行政费用,基于风险的方法仍然比 sRS 更具成本效益(IBR 总调查费用减少 40%,EBL 减少 8%),因为样本量大大减少。

结论

由于该模型依赖于通过文献回顾选择的 RF,并且通过专家估计的值进行参数化,因此它存在一定程度的不确定性。然而,这种方法为兽医当局提供了一种有前途的工具,用于未来具有成本效益的抽样设计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1590/3170209/30e4741201c3/1746-6148-7-49-1.jpg

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