Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A framework for geographical surveillance of disease in China

A framework for geographical surveillance of disease in China Purpose – The purpose of this paper is to address the urgent need for guiding the construction of information systems for disease surveillance and early warning, given the latest efforts of the report system of public health information over China. Design/methodology/approach – A system framework for disease surveillance and early warning, based on disease clustering test and cluster detection techniques, geographical information system, network and communication is conceived. Through geographical surveillance analysis of severe acute respiratory syndrome occurring in Beijing in 2003, an application example of the framework is illustrated. Findings – Through approaches such as integrating spatial‐time clustering test and cluster detection algorithms, spatial visualization, computer network, wireless communication, it is feasible to build a systematic, automatic, real‐time surveillance and early warning system for prevention and control of disease. Research limitations/implications – The present study provides an underlying framework for the development of disease surveillance and early warning system enabling data acquisition, data analysis and alarm publishing. Originality/value – The framework integrates report system of public health information, GIS and disease clustering test and cluster detection techniques into an application, which will significantly enhance the resilience of healthcare facilities. It is supposed to be implemented in near future and provides fundamental support for nation‐wide disease surveillance and early warning. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Disaster Resilience in the Built Environment Emerald Publishing

Loading next page...
 
/lp/emerald-publishing/a-framework-for-geographical-surveillance-of-disease-in-china-8GY9JWotkb

References (35)

Publisher
Emerald Publishing
Copyright
Copyright © 2011 Emerald Group Publishing Limited. All rights reserved.
ISSN
1759-5908
DOI
10.1108/17595901111167123
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to address the urgent need for guiding the construction of information systems for disease surveillance and early warning, given the latest efforts of the report system of public health information over China. Design/methodology/approach – A system framework for disease surveillance and early warning, based on disease clustering test and cluster detection techniques, geographical information system, network and communication is conceived. Through geographical surveillance analysis of severe acute respiratory syndrome occurring in Beijing in 2003, an application example of the framework is illustrated. Findings – Through approaches such as integrating spatial‐time clustering test and cluster detection algorithms, spatial visualization, computer network, wireless communication, it is feasible to build a systematic, automatic, real‐time surveillance and early warning system for prevention and control of disease. Research limitations/implications – The present study provides an underlying framework for the development of disease surveillance and early warning system enabling data acquisition, data analysis and alarm publishing. Originality/value – The framework integrates report system of public health information, GIS and disease clustering test and cluster detection techniques into an application, which will significantly enhance the resilience of healthcare facilities. It is supposed to be implemented in near future and provides fundamental support for nation‐wide disease surveillance and early warning.

Journal

International Journal of Disaster Resilience in the Built EnvironmentEmerald Publishing

Published: Oct 4, 2011

Keywords: China; Public health; Government policy; Communicable diseases; Cluster analysis; Disease surveillance; Early warning; Clustering test; Cluster detection; Programming and algorithm theory

There are no references for this article.