Statistical issues and challenges associated with rapid detection of bio-terrorist attacks
Statistical issues and challenges associated with rapid detection of bio-terrorist attacks
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DOI：
10.1002/sim.2032
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发表时间：
2005-02-28
影响因子：
2
通讯作者：
Shmueli, G
中科院分区：
文献类型：
--
作者：
Fienberg, SE;Shmueli, G
检测流行病或生物恐怖袭击爆发的传统重点是收集和分析医疗和公共卫生数据。尽管此类数据是最直接的症状指标，但它们往往是在疫情爆发后几天、几周甚至几个月收集、提供和分析的。当这些信息到达决策者手中时，往往为时已晚，无法治疗感染者或以其他方式做出反应。在本文中，我们探索了可用于及时检测生物恐怖袭击的不同数据源（传统和非传统）。我们在最先进的症状监测系统的背景下进行讨论，重点关注与非传统数据源相关的统计问题和挑战，以及出于检测目的及时整合多个数据源。版权所有 (C) 2005 John Wiley Sons, Ltd.
The traditional focus for detecting outbreaks of an epidemic or bio-terrorist attack has been on the collection and analysis of medical and public health data. Although such data are the most direct indicators of symptoms, they tend to be collected, delivered, and analysed days, weeks, and even months after the outbreak. By the time this information reaches decision makers it is often too late to treat the infected population or to react in some other way. In this paper, we explore different sources of data, traditional and non-traditional, that can be used for detecting a bio-terrorist attack in a timely manner. We set our discussion in the context of state-of-the-art syndromic surveillance systems and we focus on statistical issues and challenges associated with non-traditional data sources and the timely integration of multiple data sources for detection purposes. Copyright (C) 2005 John Wiley Sons, Ltd.