文章基本信息

标题：Performance of Early Outbreak Detection Algorithms in Public Health Surveillance from a Simulation Study
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作者：Gabriel Bedubourg ; Yann Le Strat
期刊名称：Online Journal of Public Health Informatics
电子版ISSN：1947-2579
出版年度：2016
卷号：8
期号：1
语种：English
出版社：University of Illinois at Chicago
摘要：We performed a simulation study in order to evaluate performance of 8 algorithms used in health surveillance for early outbreak detection. Each method was evaluated through its false positive rate (FPR) and its probability of detection (POD: at least one alarm during the outbreak period), for the different scenarios and outbreak sizes. Some methods have presented POD>80% and FPR<20% for the largest simulated outbreaks. For other algorithms, we observed heterogeneous performances according to simulation scenarios and outbreak sizes. Other performance criteria need to be proposed in order to improve the choice of algorithms to be implemented in health surveillance.