发现以前未见过的具有新症状模式的疫情

Yandong Liu, Daniel B. Neill
{"title":"发现以前未见过的具有新症状模式的疫情","authors":"Yandong Liu, Daniel B. Neill","doi":"10.3402/EHTJ.V4I0.11074","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":72898,"journal":{"name":"Emerging health threats journal","volume":"66 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2011-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Detecting previously unseen outbreaks with novel symptom patterns\",\"authors\":\"Yandong Liu, Daniel B. Neill\",\"doi\":\"10.3402/EHTJ.V4I0.11074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":72898,\"journal\":{\"name\":\"Emerging health threats journal\",\"volume\":\"66 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Emerging health threats journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3402/EHTJ.V4I0.11074\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Emerging health threats journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3402/EHTJ.V4I0.11074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
The Natural World Individuals and Society Hospital preparedness in community measles outbreaks-challenges and recommendations for low-resource settings. Detection of blaIMP4 and blaNDM1 harboring Klebsiella pneumoniae isolates in a university hospital in Malaysia. Two vicious circles contributing to a diagnostic delay for tuberculosis patients in Arkhangelsk.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1