Journal
JOURNAL OF BIOMEDICAL INFORMATICS
Volume 43, Issue 1, Pages 97-103Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jbi.2009.08.003
Keywords
Outbreak detection algorithms; Evaluation; Parameter values; Outbreak simulation
Funding
- Beijing Natural Science Foundation [7082047]
- Program for Excellent Talents in Beijing of China [0302600112]
- National High Technology Research and Development Program of China [2008AA02Z416]
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [0839990] Funding Source: National Science Foundation
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Background: Many researchers have evaluated the performance of outbreak detection algorithms with recommended parameter values. However, the influence of parameter values on algorithm performance is often ignored. Methods: Based on reported case counts of bacillary dysentery from 2005 to 2007 in Beijing, semi-synthetic datasets containing outbreak signals were simulated to evaluate the performance of five outbreak detection algorithms. Parameters' values were optimized prior to the evaluation. Results: Differences in performances were observed as parameter values changed. Of the five algorithms, space-time permutation scan statistics had a specificity of 99.9% and a detection time of less than half a day. The exponential weighted moving average exhibited the shortest detection time of 0.1 day, while the modified C1, C2 and C3 exhibited a detection time of close to one day. Conclusion: The performance of these algorithms has a correlation to their parameter values, which may affect the performance evaluation. (C) 2009 Elsevier Inc. All rights reserved.
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