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利用国家动物移动数据库为苏格兰应对猪病疫情提供信息:入侵时间不确定性的影响

Using national movement databases to help inform responses to swine disease outbreaks in Scotland: the impact of uncertainty around incursion time.

作者信息

Porphyre Thibaud, Boden Lisa A, Correia-Gomes Carla, Auty Harriet K, Gunn George J, Woolhouse Mark E J

机构信息

Centre for Immunity, Infection and Evolution, University of Edinburgh, King's Buildings, Edinburgh, UK.

School of Veterinary Medicine, Boyd Orr Centre for Population and Ecosystem Health, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.

出版信息

Sci Rep. 2016 Feb 1;6:20258. doi: 10.1038/srep20258.

Abstract

Modelling is an important component of contingency planning and control of disease outbreaks. Dynamic network models are considered more useful than static models because they capture important dynamic patterns of farm behaviour as evidenced through animal movements. This study evaluates the usefulness of a dynamic network model of swine fever to predict pre-detection spread via movements of pigs, when there may be considerable uncertainty surrounding the time of incursion of infection. It explores the utility and limitations of animal movement data to inform such models and as such, provides some insight into the impact of improving traceability through real-time animal movement reporting and the use of electronic animal movement databases. The study concludes that the type of premises and uncertainty of the time of disease incursion will affect model accuracy and highlights the need for improvements in these areas.

摘要

建模是疾病爆发应急规划与控制的重要组成部分。动态网络模型被认为比静态模型更有用,因为它们能够捕捉农场行为的重要动态模式,这一点已通过动物移动得到证实。本研究评估了猪瘟动态网络模型在预测感染入侵时间可能存在相当大不确定性时,通过猪的移动进行检测前传播的有用性。它探讨了动物移动数据在为这类模型提供信息方面的效用和局限性,从而对通过实时动物移动报告和使用电子动物移动数据库来提高可追溯性的影响提供了一些见解。研究得出结论,场所类型和疾病入侵时间的不确定性将影响模型准确性,并强调了在这些领域进行改进的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6a7/4735280/d56740135c9a/srep20258-f1.jpg

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