Optimizing early detection of avian influenza H5N1 in backyard and free-range poultry production systems in Thailand
Optimizing early detection of avian influenza H5N1 in backyard and free-range poultry production systems in Thailand
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DOI：
10.1016/j.prevetmed.2011.12.020
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发表时间：
2012-07-01
影响因子：
2.6
通讯作者：
Roger, Francois
中科院分区：
文献类型：
--
作者：
Goutard, Flavie L.;Paul, Mathilde;Roger, Francois
对于由H5 N1病毒（A/H5 N1 HP）引起的高致病性禽流感等传染病，预警系统至关重要。评估监测的敏感性是确保有效和可持续系统的必要步骤。随机情景树模型在这里被用来评估在泰国的后院和自由放牧鸭场的A/H5 N1 HP监测系统的敏感性。整个疾病检测监测系统的所有组件和敏感性的每个组件和整个系统的估计建模。根据高风险地区的选择、组成部分的列入和抽样程序，对各种设想方案进行了测试。全国被动监测（SSC 1）和基于风险的临床X线检查（SSC 2）显示出相似的敏感性水平，中位敏感性比值为0.96（95% CI 0.40-15.00）。它们都提供比X射线实验室组件（SSC 3）更高的灵敏度。采用当前的监测设计，当实施三个组成部分时，整个监测系统的检测灵敏度等于100%（农场水平患病率为0.05%）和82%（95% CI 71-89%）（3个农场的感染水平）。这项研究的结果表明，在发展中国家的疾病记录自由的实用性的神经树模型。(C)2012爱思唯尔有限公司版权所有。
For infectious diseases such as highly pathogenic avian influenza caused by the H5N1 virus (A/H5N1 HP), early warning system is essential. Evaluating the sensitivity of surveillance is a necessary step in ensuring an efficient and sustainable system. Stochastic scenario tree modeling was used here to assess the sensitivity of the A/H5N1 HP surveillance system in backyard and free-grazing duck farms in Thailand. The whole surveillance system for disease detection was modeled with all components and the sensitivity of each component and of the overall system was estimated. Scenarios were tested according to selection of high-risk areas, inclusion of components and sampling procedure, were tested. Nationwide passive surveillance (SSC1) and risk-based clinical X-ray (SSC2) showed a similar sensitivity level, with a median sensitivity ratio of 0.96 (95% CI 0.40-15.00). They both provide higher sensitivity than the X-ray laboratory component (SSC3). With the current surveillance design, the sensitivity of detection of the overall surveillance system when the three components are implemented, was equal to 100% for a farm level prevalence of 0.05% and 82% (95% CI 71-89%) for a level of infection of 3 farms. Findings from this study illustrate the usefulness of scenario-tree modeling to document freedom from diseases in developing countries. (C) 2012 Elsevier B.V. All rights reserved.