Literature DB >> 11279814

Infectious disease surveillance in North Rhine-Westphalia: first steps in the development of an early warning system.

R Reintjes1, H G Baumeister, D Coulombier.   

Abstract

It is often difficult to detect warning signals on infectious disease outbreaks from raw surveillance data. Data need to be used for a timely generation and distribution of information on the current state of infectious diseases. This offers the opportunity to detect outbreaks and to initiate preventive measures. To improve the surveillance system in North Rhine-Westphalia we have introduced an infectious disease barometer, a simple tool based on weekly notification data. The aim of this tool is not to provide in depth data analysis, but to help to detect clusters or outbreaks. This can be the first step in the development of an early warning system and can support epidemiological investigation and policy making.

Entities:  

Mesh:

Year:  2001        PMID: 11279814     DOI: 10.1078/S1438-4639(04)70028-0

Source DB:  PubMed          Journal:  Int J Hyg Environ Health        ISSN: 1438-4639            Impact factor:   5.840


  4 in total

1.  'Outbreak Gold Standard' selection to provide optimized threshold for infectious diseases early-alert based on China Infectious Disease Automated-alert and Response System.

Authors:  Rui-Ping Wang; Yong-Gen Jiang; Gen-Ming Zhao; Xiao-Qin Guo; Engelgau Michael
Journal:  J Huazhong Univ Sci Technolog Med Sci       Date:  2017-12-21

2.  Spatio-temporal analysis of Salmonella surveillance data in Thailand.

Authors:  A R Domingues; A R Vieira; R S Hendriksen; C Pulsrikarn; F M Aarestrup
Journal:  Epidemiol Infect       Date:  2013-10-09       Impact factor: 4.434

3.  Automated DNA sequence-based early warning system for the detection of methicillin-resistant Staphylococcus aureus outbreaks.

Authors:  Alexander Mellmann; Alexander W Friedrich; Nicole Rosenkötter; Jörg Rothgänger; Helge Karch; Ralf Reintjes; Dag Harmsen
Journal:  PLoS Med       Date:  2006-03       Impact factor: 11.069

4.  Influence of infectious disease seasonality on the performance of the outbreak detection algorithm in the China Infectious Disease Automated-alert and Response System.

Authors:  Ruiping Wang; Yonggen Jiang; Xiaoqin Guo; Yiling Wu; Genming Zhao
Journal:  J Int Med Res       Date:  2017-07-21       Impact factor: 1.671

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.