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 |
Keywords
- Evaluation
- Outbreak detection algorithms
- Outbreak simulation
- Parameter values
ASJC Scopus subject areas
- Computer Science Applications
- Health Informatics