1 Seattle JSM Session G. P. Patil August 6, 2006

2 JSM 2006 Online Program

3 Agency Databases Thematic Databases Other Databases Homeland Security Disaster Management Public Health Ecosystem Health Other Case Studies Statistical Processing: Hotspot Detection, Prioritization, etc. Data Sharing, Interoperable Middleware Standard or De Facto Data Model, Data Format, Data Access Arbitrary Data Model, Data Format, Data Access Application Specific De Facto Data/Information Standard Agency Databases Thematic Databases Other Databases Homeland Security Disaster Management Public Health Ecosystem Health Other Case Studies Statistical Processing: Hotspot Detection, Prioritization, etc. Data Sharing, Interoperable Middleware Standard or De Facto Data Model, Data Format, Data Access Arbitrary Data Model, Data Format, Data Access Application Specific De Facto Data/Information Standard National Applications Biosurveillance Carbon Management Coastal Management Community Infrastructure Crop Surveillance Disaster Management Disease Surveillance Ecosystem Health Environmental Justice Environmental Management Environmental Policy Homeland Security Invasive Species Poverty Policy Public Health Public Health and Environment Robotic Networks Sensor Networks Social Networks Syndromic Surveillance Tsunami Inundation Urban Crime Water Management Statistical Geoinformatics of Hotspot Detection, Prioritization, Early Warning, and Management NSF Digital Government Project # PI: G. P. Patil Federal Agency Partnership CDCDOD EPANASA NIHNOAA USFSUSGS Websites: NSF Digital Government hotspot geoinformatics project, federal agency partnership, and national applications for digital governance.

4 Geographic and Network Surveillance for Arbitrarily Shaped Hotspots Overview Geospatial Surveillance Upper Level Set Scan Statistic System Spatial-Temporal Surveillance Typology of Space-Time Hotspots Hotspot Prioritization Ranking Without Having to Integrate Multiple Indicators Statistical Geoinformatics for Hotspot Detection, Prioritization, Early Warning and Sustainable Management Upper Level Set Scan System Definition: A hotspot is that portion of the study region with an elevated risk of an adverse outcome Federal Agency Partnerships CDC DOD EPA NASA NIH NOAA USFS USGS Features of ULS Scan Statistic: Identifies arbitrarily shaped hotspots Applicable to data on a network Confidence sets and hotspot ratings Computationally efficient Generalizes to space-time scan Poset Prioritization System Objective: Prioritize or rank hotspots based on multiple indicator and stakeholder criteria without having to integrate indicators into an index, using Haase diagrams and partially ordered sets. Example: Prioritization of disease clusters with Multiple Indicators National Applications and Case Studies Biosurveillance Carbon Management Costal Management Community Infrastructure Crop Surveillance Disaster Management Disease Surveillance Ecosystem Health Environmental Justice Sensor Networks Robotic Networks Environmental Management Environmental Policy Homeland Security Invasive Species Poverty Policy Public Health Public Health and Environment Syndromic Surveillance Social Networks Stream Networks g Changing Connectivity of ULS as Level Drops G.P. Patil, R. Acharya, M. Haran, W.L. Myers, and P. Patankar The Pennsylvania State University R. Modarres George Washington University Example: West Nile Virus First isolated in 1937, this mosquito born disease, indigenous to north Africa, the Middle East and west Asia was first introduced into the United States in Disease Count Quintiles Population Quintiles Disease Rate QuintilesLikelihood Quintiles Comparison of ULS Scan with Circular Scan ULS ScanCircular Scan Confidence set for ULS Hotspot Hotspot Membership Rating Example: Lyme Disease Infections from the bacterium Borelia burgdorfei vectored by ticks from the genus Ixodes. ULS Scan Cylindrical Scan Example: Human-environment indicator values for 16 European countries. There are a total of 3,764,448 admissible linear extensions. The cumulative rank function for Sweden exceeds that of all remaining countries. The crf’s of all countries dominate that of Ireland. The remaining countries cannot be uniquely ordered based on their crf’s. Belgium, Netherlands and United Kingdom have identical crf’s. Admissible linear extensions are comprised of rankings compatible with the rankings of all indicators. Treating each linear extension as a voter, the cumulative rank function is obtained from the frequencies at which each object receives each rank. Disease Rates Comparison of ULS Scan with Cylindrical Scan Year Haase Diagram The crf’s also form a partially ordered set. There are only 182 admissible linear extensions for this poset, yielding the cumulative rank function: One more iteration yields the rankings in the data table. Center for Statistical Ecology and Environmental Statistics S.L. Rathbun University of Georgia

5 NSF Digital Government hotspot geoinformatics project, federal agency partnership, and national applications for digital governance. - Publications - G. P. Patil and C. Taillie (2003). Geographic and network surveillance via scan statistics for critical area detection. Statistical Science, 18 (4), G.P.Patil (2003). BOF Report: Geoinformatic surveillance: Hotspot detection and prioritization across geographic regions and networks for digital government in the 21st century. In: Proceedings of the 4th Annual International Conference on Digital Government Research, Boston, MA, May 18-22, 2003, pp G. P. Patil and C. Taillie. (2004a). Upper level set scan statistic for detecting arbitrarily shaped hotspots. Environmental and Ecological Statistics, 11 (2), G. P. Patil and C. Taillie (2004b). Multiple indicators, partially ordered sets, and linear extensions: Multi-criterion ranking and prioritization. Environmental and Ecological Statistics, 11 (2), G.P. Patil and C. Taillie (2004c). Geoinformatic surveillance hotspot prioritization using linear extensions of partially ordered sets for multi-criterion ranking with multiple indicators. In: Proceedings of the 5th Annual International Conference on Digital Government Research, Seattle, WA, May 24-26, 2004, pp G.P.Patil, S. Rathbun, R. Acharya, P. Patankar, R. Modarres (2005). Upper Level Set Scan System for Detecting Arbitrarily Shaped Hotspots for Digital Governance, In: Proceedings of the 6th Annual International Conference on Digital Government Research, Atlanta, GA, May 18-25, 2005, pp G. P. Patil, R. Modarres, W.L. Myers, P. Patankar (2006a). Spatially Constrained Clustering and Upper Level Set Scan Hotspot Detection in Surveillance Geometrics. Environmental and Ecological Statistics, Special Institutional Thematic Issue: Penn State Cross-Disciplinary Classroom in Statistical Ecology and Environmental Statistics, Volume 13 (4). In press. Reza Modarres and G.P. Patil (2006b). Hotspot Detection with Bivariate Data. Journal of Statistical Planning and Inference (S.N. Roy Centennial Volume) In press. G.P. Patil, R. Acharya, R. Modarres, W.L. Myers, and S.L. Rathbun (2006c). Hotspot Geoinformatics for Digital Governance. In: Encyclopedia of Digital Government, Volume II, Idea Group Publishing, Hershey, PA, 2006, A.V. Anttiroiko, M. Malkia (Editors).

6 G.P. Patil, Raj Acharya, Amy Glasmeier, Wayne Myers, Shashi Phoha, and Stephen Rathbun (2006d). Hotspot Detection and Prioritization – Geoinformatics for Digital Governance, In: Digital Government: Advanced Research and Case Studies. Springer Publ., H. Chen. L. Brandt, V. Gregg, R. Traunmüller, S. Dawes, E. Hovy, A. Macintosh, C. Larson (Editors). G.P. Patil (2006e). Digital Governance and Hotspot Geoinformatics for Monitoring, Etiology, Early Warning, and Sustainable Management, In: Proceedings of the 7th Annual International Conference on Digital Government Research, San Diego, CA, May 21-24, 2006, p S.L. Rathbun and G.P. Patil (2006f). Spatiotemporal Geoinformatic Disease Surveillance, Joint Statistical Meetings, August 6-10, 2006, Seattle, WA. G.P. Patil, Raj Acharya, Wayne Myers, Shashi Phoha, and Rajan Zambre, Hotspot Geoinformatics for Detection, Prioritization, and Security (2006g). In: Encyclopedia of Geographical Information Science, Shashi Shekhar and Hui Xiong (Editors). G.P. Patil, K. Sham Bhat, and Michael Kase (2006h). Evaluation of Multiple Indicators for Conditions of Watersheds in the Atlantic Slope Consortium: Multicriteria Prioritization and Ranking with Differential Weights, Stepwise Aggregations, Hasse Diagrams, Poset Cumulative Rank Frequency Operators, and Markov Chain Monte Carlo Methods. Center for Statistical Ecology and Environmental Statistics Technical Report Number , The Pennsylvania State University, University Park, PA. G.P. Patil, Jessica Newlin, K. Sham Bhat, and Michael Kase (2006i). Evaluation of Multiple Indicators for Stream Channel Stability Near Bridges in the United States: Multi-Criteria Prioritization and Ranking with Differential Weights, Stepwise Aggregation, Hasse Diagrams, Poset Cumulative Rank Frequency Operators, and Markov Chain Monte Carolo Methods. Center for Statistical Ecology and Environmental Statistics Technical Report Number , The Pennsylvania State University, University Park, PA. G.P. Patil and K. Sham Bhat (2006j). Unmasking Weight Camouflage of a Composite Index Based on Multiple Indicators. Center for Statistical Ecology and Environmental Statistics Technical Report Number The Pennsylvania State University, University Park, PA. Wayne L. Myers and Ganapati P. Patil (2006k). Partial Order and Rank Range Runs for Compositional Complexes. Center for Statistical Ecology and Environmental Statistics Technical Report Number , The Pennsylvania State University, University Park, PA. G.P. Patil, R. Bruggemann, and A. Warke (2006l). On Multicriteria Prioritization and Ranking, Using Posets, Hasse Diagrams, and Monte Carlo Algorithms with Applications—A Comparative Study (in preparation).

7 Publications in Press Springer Environmental and Ecological Statistics Monographs Series Editors: G.P. Patil, T. Gregoire, Andrew Lawson Volume 1: Landscape Pattern Analysis for Assessing Ecosystem Condition By G. D. Johnson and G. P. Patil Volume 2: Pattern-Based Compression of Multi-Band Image Data for Landscape Analysis By W. L. Myers and G. P. Patil Springer Journal on Environmental and Ecological Statistics Editor-in-Chief: G.P. Patil Deputy Editor: T. Gregoire Special Issue 1: Hotspot Geoinformatics: December 2004 Special Issue 2: Hotspot Geoinformatics: December 2006