发现以前未见过的具有新症状模式的疫情

Yandong Liu, Daniel B. Neill
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引用次数: 12

摘要

常用的基于空间扫描统计的综合征监测方法(1)首先将疾病病例划分为广泛的、先前存在的症状类别(前驱症状),如呼吸道或发热,然后发现最近某些前驱症状病例数异常高的空间聚集性。新出现的感染可能具有非常特殊和异常的症状,即使病例数量很少,也应该很容易发现。然而,如果所产生的病例不属于任何已知的前驱症状,典型的空间扫描方法可能无法检测到新的疫情。另一种情况是,由于将病例集中在一个过于宽泛的前驱症状中,稀释了疫情信号,可能会延迟发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting previously unseen outbreaks with novel symptom patterns
Introduction Commonly used syndromic surveillance methods based on the spatial scan statistic (1) first classify disease cases into broad, preexisting symptom categories (prodromes) such as respiratory or fever, then detect spatial clusters where the recent case count of some prodrome is unexpectedly high. Novel emerging infections may have very specific and anomalous symptoms, which should be easy to detect even if the number of cases is small. However, typical spatial scan approaches may fail to detect a novel outbreak if the resulting cases are not classified to any known prodrome. Alternatively, detection may be delayed because cases are lumped into an overly broad prodrome, diluting the outbreak signal.
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