当前位置: X-MOL 学术Annu. Rev. Phytopathol. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Surveillance to Inform Control of Emerging Plant Diseases: An Epidemiological Perspective
Annual Review of Phytopathology ( IF 9.1 ) Pub Date : 2017-08-04 00:00:00 , DOI: 10.1146/annurev-phyto-080516-035334
Stephen Parnell 1 , Frank van den Bosch 2 , Tim Gottwald 3 , Christopher A. Gilligan 4
Affiliation  

The rise in emerging pathogens and strains has led to increased calls for more effective surveillance in plant health. We show how epidemiological insights about the dynamics of disease spread can improve the targeting of when and where to sample. We outline some relatively simple but powerful statistical approaches to inform surveillance and describe how they can be adapted to include epidemiological information. This enables us to address questions such as: Following the first report of an invading pathogen, what is the likely incidence of disease? If no cases of disease have been found, how certain can we be that the disease was not simply missed by chance? We illustrate the use of spatially explicit stochastic models to optimize targeting of surveillance and control resources. Finally, we discuss how modern detection and diagnostic technologies as well as information from passive surveillance networks (e.g., citizen science) can be integrated into surveillance strategies.

中文翻译:


监测以控制新兴植物病害:流行病学的角度

新兴病原体和菌株的增加导致对植物健康进行更有效监控的呼声越来越高。我们展示了有关疾病传播动态的流行病学见解如何可以提高针对何时何地进行采样的目标。我们概述了一些相对简单但功能强大的统计方法来为监视提供信息,并描述如何将其修改为包括流行病学信息。这使我们能够解决以下问题:在首次报告入侵的病原体之后,疾病的可能发病率是多少?如果没有发现疾病病例,我们如何确定该疾病不是偶然被遗漏的呢?我们说明了使用空间显式随机模型来优化监视和控制资源的目标。最后,

更新日期:2017-08-04
down
wechat
bug