文章基本信息

标题：Contextualizing Data Streams for Infectious Disease Surveillance
本地全文：下载
作者：Kirsten Taylor-McCabe ; Lauren Castro ; Nicholas Generous 等
期刊名称：Online Journal of Public Health Informatics
电子版ISSN：1947-2579
出版年度：2014
卷号：6
期号：1
语种：English
出版社：University of Illinois at Chicago
摘要：To aid in developing a global biosurveillance program, it is critical to develop a framework to capture and understand the myriad of data streams and evaluate them in context of surveillance goals. Toward this goal, Los Alamos National Laboratory has developed a new method of evaluating the effectiveness of data stream types through the use of a novel concept called the surveillance window, a technique that integrates operational systems analysis, surveillance system analysis and epidemiological analysis. This study provides a simple, yet elegant methodology for which to ground truth known and emerging data streams for utility in integrated biosurveillance efforts.