Automated outbreak detection: a quantitative retrospective analysis
Automated outbreak detection: a quantitative retrospective analysis
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DOI：
10.1017/s0950268898001939
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发表时间：
1999-02-01
影响因子：
4.2
通讯作者：
Lightfoot, D
中科院分区：
文献类型：
--
作者：
Stern, L;Lightfoot, D
已经开发了一个自动预警系统，用于检测人类肠道病原体感染的集群。所使用的方法不需要特定的疾病建模，并有可能扩展到其他流行病学的应用。复合平滑技术用于从过去的数据确定疾病的基线“正常”发病率，并且通过将从基线统计确定的增量与固定的最小阈值相结合来产生当前数据的警告阈值。对3年以上的沙门氏菌感染进行了回顾性研究。在此期间，自动化系统实现了> 90%的灵敏度，阳性预测值始终> 50%，证明了统计和启发式方法组合用于聚类检测的有效性。我们建议，定量测量是相当大的效用，在评估这样的系统的性能。
An automated early warning system has been developed and used for detecting clusters of human infection with enteric pathogens. The method used requires no specific disease modelling, and has the potential for extension to other epidemiological applications. A compound smoothing technique is used to determine baseline 'normal' incidence of disease from past data, and a warning threshold for current data is produced by combining a statistically determined increment from the baseline with a fixed minimum threshold. A retrospective study of salmonella infections over 3 years has been conducted. Over this period, the automated system achieved > 90 % sensitivity, with a positive predictive value consistently > 50 %, demonstrating the effectiveness of the combination of statistical and heuristic methods for cluster detection. We suggest that quantitative measurements are of considerable utility in evaluating the performance of such systems.