Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 97-103 |
| Number of pages | 7 |
| Journal | Journal of Biomedical Informatics |
| Volume | 43 |
| Issue number | 1 |
| DOIs | |
| State | Published - Feb 2010 |
| Externally published | Yes |
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Keywords
- Evaluation
- Outbreak detection algorithms
- Outbreak simulation
- Parameter values
ASJC Scopus subject areas
- Computer Science Applications
- Health Informatics
Cite this
Comparing early outbreak detection algorithms based on their optimized parameter values. / Wang, Xiaoli; Zeng, Dajun; Seale, Holly; Li, Su; Cheng, He; Luan, Rongsheng; He, Xiong; Pang, Xinghuo; Dou, Xiangfeng; Wang, Quanyi.
In: Journal of Biomedical Informatics, Vol. 43, No. 1, 02.2010, p. 97-103.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Comparing early outbreak detection algorithms based on their optimized parameter values
AU - Wang, Xiaoli
AU - Zeng, Dajun
AU - Seale, Holly
AU - Li, Su
AU - Cheng, He
AU - Luan, Rongsheng
AU - He, Xiong
AU - Pang, Xinghuo
AU - Dou, Xiangfeng
AU - Wang, Quanyi
PY - 2010/2
Y1 - 2010/2
N2 - 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.
AB - 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.
KW - Evaluation
KW - Outbreak detection algorithms
KW - Outbreak simulation
KW - Parameter values
UR - http://www.scopus.com/inward/record.url?scp=74649084204&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=74649084204&partnerID=8YFLogxK
U2 - 10.1016/j.jbi.2009.08.003
DO - 10.1016/j.jbi.2009.08.003
M3 - Article
VL - 43
SP - 97
EP - 103
JO - Journal of Biomedical Informatics
JF - Journal of Biomedical Informatics
SN - 1532-0464
IS - 1
ER -