From molecular to genomic epidemiology: transforming surveillance and control of infectious diseases.

From molecular to genomic epidemiology: transforming surveillance and control of infectious diseases.
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从分子流行病学到基因组流行病学:改变传染病的监测和控制。

DOI:
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发表时间:
2013
期刊:
Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin
影响因子:
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通讯作者:
S. Brisse
S. Brisse
中科院分区:
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文献类型:
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作者:
M. Struelens;S. Brisse

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使用功能日益强大的基因分型工具来鉴定病原体已成为传染病监测和疫情调查的标准组成部分。本期《欧洲监测》专题杂志分两部分出版,提供了一系列综述和原创研究文章,评估了分子流行病学策略和工具的进展,并说明了它们在公共卫生中的应用。传染病分子流行病学将传统的流行病学方法与在人群和相关宿主中分析病原体随时间、地点和人的基因组多态性相结合,研究宿主-病原体相互作用,推断宿主-宿主或源-宿主传播的假设[1-3]。基于对人类病原体的区别性基因分型,克隆衍生菌株可被确定为传播链中的可能环节[1-3]。在本期由两部分组成的《欧洲监测》杂志中,Goering等人解释说,这种克隆联系的生物学证据是对人际接触或共同暴露于潜在传染源bbb的流行病学证据的补充,但不能取代。Muellner等人提供了明确的例子,说明如何通过整合病原体遗传信息和流行病学建模来增强对传染病结果和传播风险的预测,从而为有关食源性疾病预防的公共卫生决策提供信息[10]。
The use of increasingly powerful genotyping tools for the characterisation of pathogens has become a standard component of infectious disease surveillance and outbreak investigations. This thematic issue of Eurosurveillance, published in two parts, provides a series of review and original research articles that gauge progress in molecular epidemiology strategies and tools, and illustrate their applications in public health. Molecular epidemiology of infectious diseases combines traditional epidemiological methods with analysis of genome polymorphisms of pathogens over time, place and person across human populations and relevant reservoirs, to study host–pathogen interactions and infer hypotheses about host-to-host or source-to-host transmission [1-3]. Based on discriminant genotyping of human pathogens, clonally derived strains can be identified as likely links in a chain of transmission [1-3]. In this two-part issue of Eurosurveillance, Goering et al. explain that such biological evidence of clonal linkage complements but does not replace epidemiological evidence of personto-person contact or common exposure to a potential source [3]. Muellner et al. provide clear examples how prediction about infectious disease outcome and transmission risks can be enhanced through integration of pathogen genetic information and epidemiological modelling to inform public health decisions about food-borne disease prevention [4].
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