Expectation-based scan statistics for monitoring spatial time series data

International Journal of Forecasting

Volumn 25, Issue 3, 2009, Pages 498-517

  Neill, Daniel B ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

Biosurveillance; Event detection; Pattern detection; Spatial scan statistics; Time series monitoring

Indexed keywords

EID: 67449160454     PISSN: 01692070     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijforecast.2008.12.002     Document Type: Article

References (41)

1. Ailamaki A., Faloutsos C., Fischbeck P., Small M., and VanBriesen J. An environmental sensor network to determine drinking water quality and security. SIGMOD Record 32 4 (2003) 47-52
2. Brown R.G. Statistical forecasting for inventory control (1959), McGraw-Hill
3. Buckeridge D.L., Burkom H.S., Moore A.W., Pavlin J.A., Cutchis P.N., and Hogan W.R. Evaluation of syndromic surveillance systems: Development of an epidemic simulation model. Morbidity and Mortality Weekly Report 53 (2004) 137-143 (Supplement on Syndromic Surveillance)
4. Burkom H.S., Murphy S.P., Coberly J., and Hurt-Mullen K. Public health monitoring tools for multiple data streams. Morbidity and Mortality Weekly Report 54 (2005) 55-62 (Supplement on Syndromic Surveillance)
5. Burkom H.S., Murphy S.P., and Shmueli G. Automated time series forecasting for biosurveillance. Statistics in Medicine 26 22 (2007) 4202-4218
6. Corcoran J.J., Wilson I.D., and Ware J.A. Predicting the geo-temporal variations of crime and disorder. International Journal of Forecasting 19 (2003) 623-634
7. Davies, R., for the ECADS partners and collaborator (2006). Detection of Walkerton gastroenteritis outbreak using syndromic surveillance of emergency room records. Advances in Disease Surveillance, 1, 20
8. Duczmal L., and Assuncao R. A simulated annealing strategy for the detection of arbitrary shaped spatial clusters. Computational Statistics and Data Analysis 45 (2004) 269-286
9. Duczmal L., Kulldorff M., and Huang L. Evaluation of spatial scan statistics for irregularly shaped clusters. Journal Computational & Graphical Statistics 15 2 (2006) 428-442
10. Fawcett, T., & Provost, F. (1999). Activity monitoring: Noticing interesting changes in behavior. In Proceedings of the 5th international conference on knowledge discovery and data mining (pp. 53-62)
11. Gorr W., and Harries R. Introduction to crime forecasting. International Journal of Forecasting 19 (2003) 551-555
12. Hjalmars U., Kulldorff M., Gustafsson G., and Nagarwalla N. Childhood leukemia in Sweden: Using GIS and a spatial scan statistic for cluster detection. Statistics in Medicine 15 (1996) 707-715
13. Hotelling H.H. Multivariate quality control. In: Eisenhart C., Hastay M.W., and Wallis W.A. (Eds). Techniques of statistical analysis (1947), McGraw-Hill, New York 111-184
14. Kleinman K., Abrams A., Kulldorff M., and Platt R. A model-adjusted space-time scan statistic with an application to syndromic surveillance. Epidemiology and Infection 133 3 (2005) 409-419
15. Kulldorff M. A spatial scan statistic. Communications in Statistics: Theory and Methods 26 6 (1997) 1481-1496
16. Kulldorff M. Prospective time-periodic geographical disease surveillance using a scan statistic. Journal of the Royal Statistical Society A 164 (2001) 61-72
17. Kulldorff M., Athas W., Feuer E., Miller B., and Key C. Evaluating cluster alarms: A space-time scan statistic and cluster alarms in Los Alamos. American Journal of Public Health 88 (1998) 1377-1380
18. Kulldorff M., Feuer E.J., Miller B.A., and Freedman L.S. Breast cancer clusters in the northeast United States: A geographic analysis. American Journal of Epidemiology 146 2 (1997) 161-170
19. Kulldorff M., Heffernan R., Hartman J., Assuncao R., and Mostashari F. A space-time permutation scan statistic for the early detection of disease outbreaks. PLoS Medicine 2 3 (2005) e59
20. Kulldorff M., Huang L., Pickle L., and Duczmal L. An elliptic spatial scan statistic. Statistics in Medicine 25 (2006) 3929-3943
21. Kulldorff M., and Nagarwalla N. Spatial disease clusters: Detection and inference. Statistics in Medicine 14 (1995) 799-810
22. Levine, N. (1999). CrimeStat: A spatial statistics program for the analysis of crime incident locations. National Institute of Justice, Washington, DC
23. Mostashari F., Kulldorff M., Hartman J.J., Miller J.R., and Kulasekera V. Dead bird clustering: A potential early warning system for West Nile virus activity. Emerging Infectious Diseases 9 (2003) 641-646
24. Neill, D. B. (2006). Detection of spatial and spatio-temporal clusters. Tech. rep CMU-CS-06-142. Ph.D. thesis. Carnegie Mellon University, Department of Computer Science
25. Neill D.B. An empirical comparison of spatial scan statistics for outbreak detection. Advances in Disease Surveillance 4 (2007) 259
26. Neill D.B., and Lingwall J. A nonparametric scan statistic for multivariate disease surveillance. Advances in Disease Surveillance 4 (2007) 106
27. Neill, D. B., & Moore, A. W. (2005). Anomalous spatial cluster detection. In Proceedings of KDD 2005 workshop on data mining methods for anomaly detection (pp. 41-44)
28. Neill D.B., Moore A.W., and Cooper G.F. A Bayesian spatial scan statistic. Advances in Neural Information Processing Systems 18 (2006) 1003-1010
29. Neill D.B., Moore A.W., and Cooper G.F. A multivariate Bayesian scan statistic. Advances in Disease Surveillance 2 (2007) 60
30. Neill D.B., Moore A.W., and Sabhnani M.R. Detecting elongated disease clusters. Morbidity and Mortality Weekly Report 54 (2005) 197 (Supplement on Syndromic Surveillance)
31. Neill, D. B., Moore, A. W., Sabhnani, M. R., & Daniel, K. (2005b). Detection of emerging space-time clusters. In Proceedings of the 11th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 218-227)
32. Neill D.B., and Sabhnani M.R. A robust expectation-based spatial scan statistic. Advances in Disease Surveillance 2 (2007) 61
33. Neill, D. B., & Moore, A. W. (2004). Rapid detection of significant spatial clusters. In Proceedings of the 10th ACM SIGKDD conference on knowledge discovery and data mining (pp. 256-265)
34. Neill D.B., Moore A.W., Pereira F., and Mitchell T. Detecting significant multidimensional spatial clusters. Advances in Neural Information Processing Systems 17 (2005) 969-976
35. Page E.S. Continuous inspection schemes. Biometrika 41 (1954) 100-115
36. Patil G.P., and Taillie C. Upper level set scan statistic for detecting arbitrarily shaped hotspots. Environmental and Ecological Statistics 11 (2004) 183-197
37. Sabhnani, M. R., Neill, D. B., Moore, A. W., Tsui, F. C., Wagner, M. M., & Espino, J. U. (2005). Detecting anomalous clusters in pharmacy retail data. In Proceedings of the KDD 2005 workshop on data mining methods for anomaly detection(pp. 58-61)
38. Shewhart W.A. Economic control of quality of manufactured product (1931), Van Nostrand, New York
39. Tango T., and Takahashi K. A flexibly shaped spatial scan statistic for detecting clusters. International Journal of Health Geographics 4 (2005) 11
40. Trigg D.W. Monitoring a forecasting system. Operations Research Quarterly 15 (1964) 271-274
41. Wallstrom G.L., Wagner M.M., and Hogan W.R. High-fidelity injection detectability experiments: A tool for evaluation of syndromic surveillance systems. Morbidity and Mortality Weekly Report 54 (2005) 85-91 (Supplement on Syndromic Surveillance)