1. Hotspot Detection, Delineation, and Prioritization for Geographic Surveillance and Early Warning Organizer and Chair : G. P. Patil  2:00—2:05 Chair  2:05—2:30Upper Level Set Scan Statistic for Detecting Arbitrarily Shaped Hotspots C. Taillie and G. P. Patil  2:30—2:55 An Elliptic Scan Statistic for Geographical Disease Surveillance Martin Kulldorff, Lan Huang, and Linda Pickle  2:55—3:20 A Simulated Annealing Strategy for the Detection of Irregularly Shaped Spatial Clusters Luiz Duczmal and Renato Assuncao  3:20—3:40 Discussant: Daniel Wartenberg  3:40—3:50 Floor Discussion

2. This report is very disappointing. What kind of software are you using?

3. Stone-Age Space-Age Syndrome Stone-age data Space-age data Stone-age analysis Space-age analysis

4. Issues

5. Geospatial Surveillance

6. Spatial Temporal Surveillance

7. Crisis-Index Surveillance

8. Hotspot Prioritization

9. MARMAP System Partnership A primary purpose of MARMAP System Partnership is to develop sound methodology and appropriate software for the quantitative analysis and interpretation of multi-categorical raster maps and cellular surfaces (inferential geospatial informatics) involving landscape pattern analysis, multiscale landcover landuse change detection, accuracy assessment, critical area detection and delineation, disease mapping and geographic surveillance, prioritization and ranking without having to integrate multiple indicators, and a few more. It will be nice to see you participate in one capacity or the other. The following websites may be of particular interest at this time, giving recent publications together with current exciting events. Please feel free also to share this material with your potentially interested friends and colleagues. 1.MARMAP and MARMAP Prospectus 1, 2, 3, 4, 5, 6, 7. 2. Multiscale Advanced Raster Map Analysis System: Definition, Design, and Development. Invited Paper for Joint Statistical Meetings (New York City), Portuguese Statistical Congress, International Environmetrics Society, Brazilian Ecological Congress, and Italian Ecological Society. 3. Project MARMAP System Partnership Collaboration with EPA STAR Grant Atlantic Slope Consortium for Development, Testing, and Application of Ecological and Socioeconomic Indicators for Integrated Assessment of Atlantic Slope in the mid-Atlantic states. Website: http://es.epa.gov/ncer_abstracts/grants/00/envind/brooks.html 4. Project MARMAP System Partnership Collaboration with UNEP Division of Early Warning and Assessment on Human Environment Index based on Countrywide Land, Air, and Water Indicators. 5. Project MARMAP Show and Tell Seminar series: EPA ORD NCEA, EPA ORD NERL, EPA OEI, NASA HQ, NASA GSFC, NCHS, NYSDEH; UMD, GWU, UCB, MSU, UM, SUNY SPH. Powerpoint Presentations

10. 6. Ecosystem Health and Its Measurement at Landscape Scale: Towards the Next Generation of Quantitative Assessments. Ecosystem Health, 7(4):307—316. http://www.stat.psu.edu/~gpp/PDFfiles/TR2002-0202.pdf http://www.stat.psu.edu/~gpp/PDFfiles/TR2002-0202.pdf 7. Multiscale Advanced Raster Map Analysis System for Measurement of Ecosystem Health at Landscape Scale: A Novel Synergistic Consortium Initiative. In Managing for Healthy Ecosystems, D. Rapport, W. Lasley, D. Rolston, O. Nielsen, C. Qualset, and A. Damania, eds. CRC Press/Lewis Press. 2003. pp. 567—576. http://www.stat.psu.edu/~gpp/PDFfiles/TR2002-0301.pdf 8. Detection and Delineation of Critical Areas Using Echelon and Spatial Scan Statistics with Synoptic Cellular Data. Environmental and Ecological Statistics, 2004 (to appear). http://www.stat.psu.edu/~gpp/PDFfiles/TR2002-0501.pdf 9. Use of landscape and land use parameters for classification and characterization of watersheds in the Mid-Atlantic across five physiographic provinces. Healthy Ecosystems, Healthy People Conference, International Society for Ecosystem Health, Washington, DC. Environmental and Ecological Statistics, 2004 (to appear). 10. Finding upper level sets in cellular surface data using echelons and SaTScan. Environmental and Ecological Statistics, 2004 (to appear). http://www.stat.psu.edu/~gpp/PDFfiles/TR2002-0801.pdf

11. Geographic Surveillance and Hotspot Detection for Homeland Security: Cyber Security and Computer Network Diagnostics Geographic Surveillance and Hotspot Detection for Homeland Security: Cyber Security and Computer Network Diagnostics Securing the nation's computer networks from cyber attack is an important aspect of Homeland Security. Project develops diagnostic tools for detecting security attacks, infrastructure failures, and other operational aberrations of computer networks. Geographic Surveillance and Hotspot Detection for Homeland Security: Tasking of Self-Organizing Surveillance Mobile Sensor Networks Geographic Surveillance and Hotspot Detection for Homeland Security: Tasking of Self-Organizing Surveillance Mobile Sensor Networks Many critical applications of surveillance sensor networks involve finding hotspots. The upper level set scan statistic is used to guide the search by estimating the location of hotspots based on the data previously taken by the surveillance network. Geographic Surveillance and Hotspot Detection for Homeland Security: Drinking Water Quality and Water Utility Vulnerability Geographic Surveillance and Hotspot Detection for Homeland Security: Drinking Water Quality and Water Utility Vulnerability New York City has installed 892 drinking water sampling stations. Currently, about 47,000 water samples are analyzed annually. The ULS scan statistic will provide a real-time surveillance system for evaluating water quality across the distribution system. Geographic Surveillance and Hotspot Detection for Homeland Security: Surveillance Network and Early Warning Geographic Surveillance and Hotspot Detection for Homeland Security: Surveillance Network and Early Warning Emerging hotspots for disease or biological agents are identified by modeling events at local hospitals. A time-dependent crisis index is determined for each hospital in a network. The crisis index is used for hotspot detection by scan statistic methods Geographic Surveillance and Hotspot Detection for Homeland Security: West Nile Virus: An Illustration of the Early Warning Capability of the Scan Statistic Geographic Surveillance and Hotspot Detection for Homeland Security: West Nile Virus: An Illustration of the Early Warning Capability of the Scan Statistic West Nile virus is a serious mosquito-borne disease. The mosquito vector bites both humans and birds. Scan statistical detection of dead bird clusters provides an early crisis warning and allows targeted public education and increased mosquito control. Geographic Surveillance and Hotspot Detection for Homeland Security: Crop Pathogens and Bioterrorism Geographic Surveillance and Hotspot Detection for Homeland Security: Crop Pathogens and Bioterrorism Disruption of American agriculture and our food system could be catastrophic to the nation's stability. This project has the specific aim of developing novel remote sensing methods and statistical tools for the early detection of crop bioterrorism. Geographic Surveillance and Hotspot Detection for Homeland Security: Disaster Management: Oil Spill Detection, Monitoring, and Prioritization Geographic Surveillance and Hotspot Detection for Homeland Security: Disaster Management: Oil Spill Detection, Monitoring, and Prioritization The scan statistic hotspot delineation and poset prioritization tools will be used in combination with our oil spill detection algorithm to provide for early warning and spatial-temporal monitoring of marine oil spills and their consequences. Geographic Surveillance and Hotspot Detection for Homeland Security: Network Analysis of Biological Integrity in Freshwater Streams Geographic Surveillance and Hotspot Detection for Homeland Security: Network Analysis of Biological Integrity in Freshwater Streams This study employs the network version of the upper level set scan statistic to characterize biological impairment along the rivers and streams of Pennsylvania and to identify subnetworks that are badly impaired. Center for Statistical Ecology and Environmental Statistics G. P. Patil, Director

12. Website Links 1. Prospectus 8: Synoptic Surveillance http://www.stat.psu.edu/~gpp/PDFfiles/Prospectus-8.pdf http://www.stat.psu.edu/~gpp/PDFfiles/Prospectus-8.pdf 2. Prospectus 11: Network-Based Surveillance http://www.stat.psu.edu/~gpp/PDFfiles/Prospectus-11.pdf 3. Prospectus 10: Classification and Prioritization http://www.stat.psu.edu/~gpp/PDFfiles/Prospectus-10.pdf 4. Prospectus 9:Crop Surveillance http://www.stat.psu.edu/~gpp/PDFfiles/Prospectus-9.pdf 5. Prospectus Abstract Syndromic Surveillance http://www.stat.psu.edu/~gpp/PDFfiles/prospectus-12.pdf http://www.stat.psu.edu/~gpp/PDFfiles/Prospectus-11.pdf http://www.stat.psu.edu/~gpp/PDFfiles/Prospectus-10.pdf http://www.stat.psu.edu/~gpp/PDFfiles/Prospectus-9.pdf http://www.stat.psu.edu/~gpp/PDFfiles/prospectus-12.pdf 6. Poster for Geographic and Network Surveillance for Hotspots http://www.stat.psu.edu/~gpp/PDFfiles/Poster%201.pdf 7. Proof-of-Concept Paper-1 http://www.stat.psu.edu/~gpp/PDFfiles/TR2002-0501.pdf 8. Proof-of-Concept Paper-2 http://www.stat.psu.edu/~gpp/PDFfiles/TR2002-0801.pdf http://www.stat.psu.edu/~gpp/PDFfiles/TR2002-0501.pdf http://www.stat.psu.edu/~gpp/PDFfiles/TR2002-0801.pdf 9. Proof-of-Concept Paper-3 http://www.stat.psu.edu/~gpp/PDFfiles/TR2001-1204.pdf 10. Background Biographics 1 http://www.stat.psu.edu/~gpp/PDFfiles/Patil-3-page%20bio.pdf 11. Background Biographics 2 http://www.stat.psu.edu/~gpp/PDFfiles/Patil-3-page%20bio.pdf http://www.stat.psu.edu/~gpp/PDFfiles/GP%20NSF%20Bio.pdf

13. You Are Invited NSF DGP PROJECT Geoinformatic Surveillance: Hotspot Detection and Prioritization Across Geographic Regions and Networks for Digital Government in the 21st Century Geoinformatic surveillance for spatial and temporal hotspot detection and prioritization is a critical need for the 21st century Digital Government. A hotspot can mean an unusual phenomenon, anomaly, aberration, outbreak, elevated cluster, or critical area. The declared need may be for monitoring, etiology, management, or early warning. The responsible factors may be natural, accidental or intentional, with relevance to both infrastructure and homeland security. This project describes a multi-disciplinary research program based on novel methods and tools for hotspot detection and prioritization, driven by a wide variety of case studies of direct interest to several government agencies. These case studies deal with critical societal issues, such as carbon budgets, water resources, ecosystem health, public health, drinking water distribution system, persistent poverty, environmental justice, crop pathogens, invasive species, biosecurity, biosurveillance, remote sensor networks, early warning and homeland security. The geosurveillance provides an excellent opportunity, challenge, and vehicle for synergistic collaboration of computational, technical, and social scientists. Our methodology involves an innovation of the popular circle-based spatial scan statistic methodology. In particular, it employs the notion of an upper level set and is accordingly called the upper level set scan statistic, pointing to the next generation of a sophisticated analytical and computational system, effective for the detection of arbitrarily shaped hotspots along spatio-temporal dimensions. We also propose a novel prioritization scheme based on multiple indicator and stakeholder criteria without having to integrate indicators into an index, using revealing Hasse diagrams and partially ordered sets. Responding to the Government’s role and need, we propose a cross-disciplinary collaboration among federal agencies and academic researchers to design and build the prototype system for surveillance infrastructure of hotspot detection and prioritization. The methodological toolbox and the software toolkit developed will support and leverage core missions of federal agencies as well as their interactive counterparts in the society. The research advances in the allied sciences and technologies necessary to make such a system work are the thrust of this five year project. The project will have a dual disciplinary and cross-disciplinary thrust. Dialogues and discussions will be particularly welcome, leading potentially to well considered synergistic case studies. The collaborative case studies are expected to be conceptual, structural, methodological, computational, applicational, developmental, refinemental, validational, and/or visualizational in their individual thrust. For additional information, see the webpages: (1) http://www.stat.psu.edu/~gpp/PDFfiles/Prospectus%2016.pdfhttp://www.stat.psu.edu/~gpp/PDFfiles/Prospectus%2016.pdf (2) http://www.stat.psu.edu/~gpp/PDFfiles/Prospectus%2016%20overview.pdfhttp://www.stat.psu.edu/~gpp/PDFfiles/Prospectus%2016%20overview.pdf (3) http://www.stat.psu.edu/~gpp/PDFfiles/Prospectus-15-Case%20Studies.pdfhttp://www.stat.psu.edu/~gpp/PDFfiles/Prospectus-15-Case%20Studies.pdf Project address: Penn State Center for Statistical Ecology and Environmental Statistics 421 Thomas Building, Penn State University, University Park, PA 16802 Telephone: (814)865-9442; Email: gpp@stat.psu.edu

14. Hotspot Detection, Delineation, and Prioritization for Geographic Surveillance and Early Warning Organizer and Chair : G. P. Patil  2:00—2:05 Chair  2:05—2:30Upper Level Set Scan Statistic for Detecting Arbitrarily Shaped Hotspots C. Taillie and G. P. Patil  2:30—2:55 An Elliptic Scan Statistic for Geographical Disease Surveillance Martin Kulldorff, Lan Huang, and Linda Pickle  2:55—3:20 A Simulated Annealing Strategy for the Detection of Irregularly Shaped Spatial Clusters Luiz Duczmal and Renato Assuncao  3:20—3:40 Discussant: Daniel Wartenberg  3:40—3:50 Floor Discussion