A Z-Score Based Multi-level Spatial Clustering Algorithm for the Detection of Disease Outbreaks
- 509 Downloads
In this paper, we propose a Z-Score Based Multi-level Spatial Clustering (ZMSC) algorithm for the early detection of emerging disease outbreaks. Using semi-synthetic data for algorithm evaluation, we compared ZMSC with the Wavelet Anomaly Detector , a temporal algorithm, and two spatial clustering algorithms: Kulldorff’s spatial scan statistic  and Bayesian spatial scan statistic . ROC curve analysis shows that ZMSC has better discriminatory ability than the three compared algorithms. ZMSC demonstrated significant computational efficiency—1000x times faster than both spatial algorithms. Finally, ZMSC had the highest cluster positive predictive values of all the algorithms. However, ZMSC showed a 0.5-1 day average delay in detection when the false alarm rate was lower than one false alarm for every five days. We conclude that the ZMSC algorithm improves current methods of spatial cluster detection by offering better discriminatory ability, faster performance and more exact cluster identification.
KeywordsSpatial clustering outbreak detection biosurveillance
Unable to display preview. Download preview PDF.
- 1.Zhang, J., Tsui, F.C., Wagner, M.M., Hogan, W.R.: Detection of Outbreaks from Time Series Data Using Wavelet Transform. In: AMIA Annual Symposium Proceeding, pp. 748–752 (2003)Google Scholar
- 3.Neill, D.B., Moore, A.W., Cooper, G.F.: A Bayesian Spatial Scan Statistic. In: Advances in Neural Information Processing Systems, vol. 18, pp. 1003–1010 (2005)Google Scholar
- 4.Hunter, J.S.: The Exponentially Weighted Moving Average. Journal of Quality Technology 18, 155–162 (1986)Google Scholar
- 6.Wagner, M.M., Moore, A.W., Aryel, R.M.: Handbook of Biosurveillance. Elsevier, Amsterdam (2006)Google Scholar
- 9.Kunihiko, T., Martin, K., Toshiro, T., Katherine, Y.: A Flexibly Shaped Space-Time Scan Statistic for Disease Outbreak Detection and Monitoring. International Journal of Health Geographics 7(14) (2008)Google Scholar
- 11.Tango, T., Takahashi, K.: A Flexible Shaped Spatial scan Statistic for Detecting Clusters. International Journal of Health Geographics 4(11) (2005)Google Scholar
- 12.Zeng, D., Chang, W., Chen, H.: A Comparative Study of Spatio-Temporal Hotspot Analysis Techniques in Security Informatics. IEEE ITSC, 106–111 (2004)Google Scholar
- 13.Siegrist, D., Pavlin, J.: Bio-ALIRT biosurveillance detection algorithm evaluation. MMWR Morb Mortal Wkly Rep. 24(53) (suppl.), 152–158 (2004)Google Scholar
- 14.Kulldorff, M., Heffernan, R., Hartman, J., Assuncão, R., Mostashari, F.: A Space-Time Permutation Scan Statistic for Disease Outbreak Detection. PLoS medicine 2(3) (2005)Google Scholar