Evaluation of school absenteeism data for early outbreak detection, New York City.
Evaluation of school absenteeism data for early outbreak detection, New York City.
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DOI：
10.1186/1471-2458-5-105
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发表时间：
2005-10-07
影响因子：
4.5
通讯作者：
Weiss D
中科院分区：
文献类型：
--
作者：
Besculides M;Heffernan R;Mostashari F;Weiss D
学校缺勤数据可能可以作为疾病爆发的早期指标，但应严格审查其价值。本文描述了对纽约市 (NYC) 学校缺勤数据在早期疫情检测中的效用的评估。为了评估全市缺勤的时间趋势，我们从纽约市教育部 (DOE) 网站下载了三年（2001-02、2002-03、2003-04）的每日学校出勤数据。我们应用 CuSum 方法来识别调整后的每日缺勤百分比的偏差。使用空间扫描统计数据来评估 2001-02 学年缺勤的地理聚集情况。在流感高峰季节，儿童缺勤率适度增加。空间分析发现小学生中存在 790 个显着的缺勤集群 (p < 0.01)，其中两个发生在之前报告的疫情爆发期间。监测学校缺勤情况对于检测全市范围内的大规模流行病可能有一定作用，但是，学校层面的数据存在噪音，我们无法证明使用聚类分析来检测局部疫情有任何实际价值。根据这些结果，我们不会对学校缺勤数据进行前瞻性监测，但正在评估更具体的学校数据在疫情爆发检测中的效用。
School absenteeism data may have utility as an early indicator of disease outbreaks, however their value should be critically examined. This paper describes an evaluation of the utility of school absenteeism data for early outbreak detection in New York City (NYC). To assess citywide temporal trends in absenteeism, we downloaded three years (2001–02, 2002–03, 2003–04) of daily school attendance data from the NYC Department of Education (DOE) website. We applied the CuSum method to identify aberrations in the adjusted daily percent absent. A spatial scan statistic was used to assess geographic clustering in absenteeism for the 2001–02 academic year. Moderate increases in absenteeism were observed among children during peak influenza season. Spatial analysis detected 790 significant clusters of absenteeism among elementary school children (p < 0.01), two of which occurred during a previously reported outbreak. Monitoring school absenteeism may be moderately useful for detecting large citywide epidemics, however, school-level data were noisy and we were unable to demonstrate any practical value in using cluster analysis to detect localized outbreaks. Based on these results, we will not implement prospective monitoring of school absenteeism data, but are evaluating the utility of more specific school-based data for outbreak detection.
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影响因子：
0.8
作者：
Kulldorff, M
通讯作者：
Kulldorff, M
影响因子：
11.8
作者：
Heffernan, R;Mostashari, F;Weiss, D
通讯作者：
Weiss, D
影响因子：
4.2
作者：
Proctor, ME;Blair, KA;Davis, JP
通讯作者：
Davis, JP
DOI：
10.1111/1467-985x.00186
发表时间：
2001-01-01
影响因子：
2
作者：
Kulldorff, M
通讯作者：
Kulldorff, M
影响因子：
4.2
作者：
MONTO, AS;SULLIVAN, KM
通讯作者：
SULLIVAN, KM