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泰国家禽中 H5N1 的爆发:家禽生产类型在维持传播中的相对作用,以及主动监测在控制中的影响。

Outbreaks of H5N1 in poultry in Thailand: the relative role of poultry production types in sustaining transmission and the impact of active surveillance in control.

机构信息

MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.

出版信息

J R Soc Interface. 2012 Aug 7;9(73):1836-45. doi: 10.1098/rsif.2012.0022. Epub 2012 Feb 22.

Abstract

H5N1, highly pathogenic avian influenza, continues to pose a public health risk in the countries of southeast Asia where it has become endemic. However, in Thailand, which experienced two of the largest recorded epidemics in 2004-2005, the disease has been successfully reduced to very low levels. We fitted a spatio-temporal model of the spread of infection to outbreak data collected during the second wave of outbreaks to assess the extent to which different poultry types were responsible for propagating infection. Our estimates suggest that the wave of outbreaks would not have been possible without the contribution of backyard flocks to the susceptibility of a sub-district. However, we also estimated that outbreaks involving commercial poultry, a much larger sector in Thailand than in neighbouring countries, were disproportionately infectious, a factor which was also crucial in sustaining the wave. As a result, implemented measures that aim to reduce the role of commercial farms in the spread of infection, such as the drive to bring aspects of the supply chain 'in house', may help to explain the subsequent success in controlling H5N1 in Thailand. We also found that periods of active surveillance substantially improved the rate of outbreak detection.

摘要

H5N1,高致病性禽流感,在东南亚成为地方病的国家继续构成公共卫生风险。然而,在 2004-2005 年经历了两次最大规模疫情的泰国,该疾病已成功降低到非常低的水平。我们拟合了感染传播的时空模型,以评估在第二次疫情爆发期间收集的爆发数据中,不同家禽类型在传播感染方面的作用。我们的估计表明,如果没有后院禽群对一个分区的易感性的贡献,疫情爆发是不可能发生的。然而,我们还估计,涉及商业家禽的疫情爆发比泰国邻国的商业家禽更具传染性,这是维持疫情爆发的关键因素之一。因此,旨在减少商业农场在传播感染中作用的措施,例如推动将供应链的某些方面“内部化”,可能有助于解释泰国随后在控制 H5N1 方面的成功。我们还发现,积极监测的时期大大提高了疫情爆发的检测速度。

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