Traditional and syndromic surveillance of infectious diseases and pathogens.
Traditional and syndromic surveillance of infectious diseases and pathogens.
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DOI：
10.1016/j.ijid.2016.04.021
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发表时间：
2016-07
期刊：
影响因子：
--
通讯作者：
Raoult D
中科院分区：
文献类型：
--
作者：
Abat C;Chaudet H;Rolain JM;Colson P;Raoult D
列出了用于监测传染病的数据和战略。临床微生物实验室在这种监测中的作用是突出的。提供了2009年至2014年6月13日期间所描述的所有监视系统的审查。传染病仍然是世界范围内的一个主要公共卫生问题。因此，对他们的监视至关重要。目前，世界各地正在使用许多监测战略和系统。本文介绍了世界范围内用于传染病监测的数据、监测策略和监测系统的清单，重点介绍了微生物实验室在监测中的作用。审查了世界各地用于监测传染病和病原体的数据、战略和系统，以及当前的问题和趋势。根据与感染相关的时间、可用资源和监测类型确定了12类主要数据。比较了两种主要策略：疾病特异性监测和综合征监测。最后，对全世界实施的262个感染监测系统进行了登记和简要描述，重点介绍了基于实验室微生物学数据的系统。目前有大量关于感染的可用数据，随着最近新技术的出现，这些数据一直在增长。同时，随着计算机资源和网络的扩展，这些数据将使实时检测和通知感染的优化成为可能。
The data and strategies used for the surveillance of infectious diseases are listed. The role of clinical microbiology laboratories in this surveillance is highlighted. A review of all of the surveillance systems described from 2009 to June 13, 2014 is provided. Infectious diseases remain a major public health problem worldwide. Hence, their surveillance is critical. Currently, many surveillance strategies and systems are in use around the world. An inventory of the data, surveillance strategies, and surveillance systems developed worldwide for the surveillance of infectious diseases is presented herein, with emphasis on the role of the microbiology laboratory in surveillance. The data, strategies, and systems used around the world for the surveillance of infectious diseases and pathogens, along with current issues and trends, were reviewed. Twelve major classes of data were identified on the basis of their timing relative to infection, resources available, and type of surveillance. Two primary strategies were compared: disease-specific surveillance and syndromic surveillance. Finally, 262 systems implemented worldwide for the surveillance of infections were registered and briefly described, with a focus on those based on microbiological data from laboratories. There is currently a wealth of available data on infections, which has been growing with the recent emergence of new technologies. Concurrently with the expansion of computer resources and networks, these data will allow the optimization of real-time detection and notification of infections.
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影响因子：
11.8
作者：
Grein, T W;Kamara, K B;Rodier, G;Plant, A J;Bovier, P;Ryan, M J;Ohyama, T;Heymann, D L
通讯作者：
Heymann, D L
影响因子：
56.9
作者：
BARRESINOUSSI, F;CHERMANN, JC;MONTAGNIER, L
通讯作者：
MONTAGNIER, L
DOI：
10.1007/978-1-4419-6892-0_4
发表时间：
2011-01-01
期刊：
INFECTIOUS DISEASE INFORMATICS AND BIOSURVEILLANCE
影响因子：
--
作者：
Koski, Eileen
通讯作者：
Koski, Eileen
影响因子：
64.8
作者：
Morens DM;Folkers GK;Fauci AS
通讯作者：
Fauci AS
影响因子：
3.7
作者：
Lewis, Sheri L.;Feighner, Brian H.;Blazes, David L.
通讯作者：
Blazes, David L.