评估动物疾病控制规划中免于感染信心的框架。

IF 1.9 4区 农林科学 Q2 VETERINARY SCIENCES
C Fourichon, D A Graham, M Nielen, G Van Schaik, S J More, A Madouasse, A M van Roon, J Frossling, J Gethmann, M Mercat, E Agren, C Sauter-Louis, G Gunn, J Eze, R Humphry, M K Henry, M Guelbenzu, I M G Santman-Berends
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引用次数: 0

摘要

在基于结果的无感染自由度比较监测工具项目(https://www.stocfree.eu)中,构建了一个数据收集工具,以方便标准化收集输入数据,并开发了一个模型,以便对牛疾病不同控制计划(CPs)的产出进行标准化和协调的比较。STOC自由模型可用于评估畜群免受感染的概率,并确定这些畜群是否符合欧盟预先定义的基于输出的标准。之所以选择牛病毒性腹泻病毒(BVDV)作为本项目的病例病,是因为6个参与国的CPs存在多样性。使用数据收集工具收集详细的BVDV CP和危险因素信息。为了将数据纳入STOC自由模型,对关键方面和默认值进行了量化。贝叶斯隐马尔可夫模型被认为是合适的,并为BVDV CPs开发了一个模型。使用来自伙伴国家的BVDV CP真实数据对该模型进行了测试和验证,并公开提供了相应的计算机代码。STOC免费模型侧重于群体级数据,尽管在聚合到群体级后可以包括动物级数据。无STOC模型适用于地方病,因为它需要存在一些感染来估计参数并使其收敛。在已经实现无感染状态的国家,情景树模型可能是一种更合适的工具。建议进一步开展工作,将无STOC模型推广到其他疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A framework for assessing confidence in freedom from infection in animal disease control programmes.

In the Surveillance Tool for Outcome-based Comparison of FREEdom from infection (STOC free) project (https://www.stocfree.eu), a data collection tool was constructed to facilitate standardised collection of input data, and a model was developed to allow a standardised and harmonised comparison of the outputs of different control programmes (CPs) for cattle diseases. The STOC free model can be used to evaluate the probability of freedom from infection for herds in CPs and to determine whether these CPs comply with the European Union's pre-defined output-based standards. Bovine viral diarrhoea virus (BVDV) was chosen as the case disease for this project because of the diversity in CPs in the six participating countries. Detailed BVDV CP and risk factor information was collected using the data collection tool. For inclusion of the data in the STOC free model, key aspects and default values were quantified. A Bayesian hidden Markov model was deemed appropriate, and a model was developed for BVDV CPs. The model was tested and validated using real BVDV CP data from partner countries, and corresponding computer code was made publicly available. The STOC free model focuses on herd-level data, although that animal-level data can be included after aggregation to herd level. The STOC free model is applicable to diseases that are endemic, given that it needs the presence of some infection to estimate parameters and enable convergence. In countries where infection-free status has been achieved, a scenario tree model could be a better suited tool. Further work is recommended to generalise the STOC free model to other diseases.

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来源期刊
CiteScore
2.40
自引率
0.00%
发文量
22
审稿时长
>24 weeks
期刊介绍: The Scientific and Technical Review is a periodical publication containing scientific information that is updated constantly. The Review plays a significant role in fulfilling some of the priority functions of the OIE. This peer-reviewed journal contains in-depth studies devoted to current scientific and technical developments in animal health and veterinary public health worldwide, food safety and animal welfare. The Review benefits from the advice of an Advisory Editorial Board and a Scientific and Technical Committee composed of top scientists from across the globe.
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