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古巴禽流感基于风险的主动监测策略的制定。

Development of an active risk-based surveillance strategy for avian influenza in Cuba.

作者信息

Ferrer E, Alfonso P, Ippoliti C, Abeledo M, Calistri P, Blanco P, Conte A, Sánchez B, Fonseca O, Percedo M, Pérez A, Fernández O, Giovannini A

机构信息

Centro Nacional de Sanidad Agropecuaria (CENSA), San José de Las Lajas 32700, Mayabeque, Cuba.

Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise "G. Caporale", Via Campo Boario, 64100 Teramo, Italy.

出版信息

Prev Vet Med. 2014 Sep 1;116(1-2):161-7. doi: 10.1016/j.prevetmed.2014.05.012. Epub 2014 Jun 4.

Abstract

The authors designed a risk-based approach to the selection of poultry flocks to be sampled in order to further improve the sensitivity of avian influenza (AI) active surveillance programme in Cuba. The study focused on the western region of Cuba, which harbours nearly 70% of national poultry holdings and comprise several wetlands where migratory waterfowl settle (migratory waterfowl settlements - MWS). The model took into account the potential risk of commercial poultry farms in western Cuba contracting from migratory waterfowl of the orders Anseriformes and Charadriiformes through dispersion for pasturing of migratory birds around the MWS. We computed spatial risk index by geographical analysis with Python scripts in ESRI(®) ArcGIS 10 on data projected in the reference system NAD 1927-UTM17. Farms located closer to MWS had the highest values for the risk indicator pj and in total 31 farms were chosen for targeted surveillance during the risk period. The authors proposed to start active surveillance in the study area 3 weeks after the onset of Anseriformes migration, with additional sampling repeated twice in the same selected poultry farms at 15 days interval (Comin et al., 2012; EFSA, 2008) to cover the whole migration season. In this way, the antibody detectability would be favoured in case of either a posterior AI introduction or enhancement of a previous seroprevalence under the sensitivity level. The model identified the areas with higher risk for AIV introduction from MW, aiming at selecting poultry premises for the application of risk-based surveillance. Given the infrequency of HPAI introduction into domestic poultry populations and the relative paucity of occurrences of LPAI epidemics, the evaluation of the effectiveness of this approach would require its application for several migration seasons to allow the collection of sufficient reliable data.

摘要

作者设计了一种基于风险的方法来选择要采样的家禽群,以进一步提高古巴禽流感(AI)主动监测计划的敏感性。该研究聚焦于古巴西部地区,该地区拥有全国近70%的家禽养殖场,并且包含几个候鸟栖息的湿地(候鸟栖息地——MWS)。该模型考虑了古巴西部商业家禽养殖场通过在MWS周围放牧候鸟而从雁形目和鸻形目候鸟感染的潜在风险。我们使用ESRI(®) ArcGIS 10中的Python脚本对投影在NAD 1927 - UTM17参考系统中的数据进行地理分析,计算空间风险指数。距离MWS较近的养殖场风险指标pj值最高,在风险期共有31个养殖场被选作目标监测对象。作者建议在雁形目候鸟开始迁徙3周后在研究区域启动主动监测,并在选定的同一家禽养殖场每隔15天重复采样两次(Comin等人,2012年;欧洲食品安全局,2008年),以覆盖整个迁徙季节。这样一来,在出现后续禽流感引入情况或之前血清阳性率在敏感性水平以下升高时,抗体检测能力将更有优势。该模型确定了从候鸟引入禽流感病毒风险较高的区域,旨在选择家禽养殖场应用基于风险的监测。鉴于高致病性禽流感在家禽群体中引入的频率较低,以及低致病性禽流感疫情发生相对较少,评估这种方法的有效性需要在几个迁徙季节应用该方法,以便收集足够可靠的数据。

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