Infectious Disease Informatics and Biosurveillance, 2011 Integrated Series in Information Systems Series, Vol. 27

This book on Infectious Disease Informatics (IDI) and biosurveillance is intended to provide an integrated view of the current state of the art, identify technical and policy challenges and opportunities, and promote cross-disciplinary research that takes advantage of novel methodology and what we have learned from innovative applications. This book also fills a systemic gap in the literature by emphasizing informatics driven perspectives (e.g., information system design, data standards, computational aspects of biosurveillance algorithms, and system evaluation). Finally, this book attempts to reach policy makers and practitioners through the clear and effective communication of recent research findings in the context of case studies in IDI and biosurveillance, providing ?hands-on? in-depth opportunities to practitioners to increase their understanding of value, applicability, and limitations of technical solutions. This book collects the state of the art research and modern perspectives of distinguished individuals and research groups on cutting-edge IDI technical and policy research and its application in biosurveillance. The contributed chapters are grouped into three units. Unit I provides an overview of recent biosurveillance research while highlighting the relevant legal and policy structures in the context of IDI and biosurveillance ongoing activities. It also identifies IDI data sources while addressing information collection, sharing, and dissemination issues as well as ethical considerations. Unit II contains survey chapters on the types of surveillance methods used to analyze IDI data in the context of public health and bioterrorism. Specific computational techniques covered include: text mining, time series analysis, multiple data streams methods, ensembles of surveillance methods, spatial analysis and visualization, social network analysis, and agent-based simulation. Unit III examines IT and decision support for public health event response and bio-defense. Practical lessons learned in developing public health and biosurveillance systems, technology adoption, and syndromic surveillance for large events are discussed. The goal of this book is to provide an understandable interdisciplinary IDI and biosurveillance reference either used as a standalone textbook or reference for students, researchers, and practitioners in public health, veterinary medicine, biostatistics, information systems, computer science, and public administration and policy.

Chapter 1: Real-Time Public Health Biosurveillance: Systems and Policy Considerations.- Chapter 2: Designing Ethical Pratice in Biosurveillane: The Project Argus Doctrine.- Chapter 3: Using Emergency Department Data for Biosurveillance: The North Carolina Experience.- Chapter 4: Clinical Laboratory Data for Biosurveillance.- Chapter 5: Biosurveillance Based on Test Orders from Veterinary Diagnostic Labs.- Chapter 6: Markov Switching Models for Outbreak Detection.- Chapter 7: Detection of Events in Multiple Streams of Surveillance Data: Multivariate, Multi-stream and Multidimensional Approaches.- Chapter 8: Algorithm Combination for Improved Performance in Biosurveillance: Algorithms Combination for Improved Surveillance.- Chapter 9: Modeling in Space and Time: A Framework for Visualization and Collaboration.- Chapter 10: Surveillance of Infectious Diseases Using Spatial and Temporal Clustering Methods: Spatial and Temporal Clustering Methods Used in Epidemiology of Infectious Diseases.- Chapter 11: Age-Adjustment in National Biosurveillance Systems: A Survey of Issues and Analytical Tools for Age-adjustment in Biosurveillance.- Chapter 12: Modeling in Immunization and Biosurveillance.- Chapter 13: Natural Language Processing for Biosurveillance: Detection and Characterization from Textual Clinical Reports.- Chapter 14: Knowledge Mapping for Bioterrorism-related Literature.- Chapter 15: Social Networking Analysis for Contract Tracing.- Chapter 16: Multi-Agent Modeling of Biological and Chemical Threats.- Chapter 17: Integrated Health Altering and Notification: A Case Study in New York State.- Chapter 18: Design and Performance of a Public Health Preparedness Informatics Framework.- Chapter 19: System Evaluation and User Technology Adoption: A Case Study of BioPortal.- Chapter 20: Syndromic Surveillance for the G8 Hokkaido Toyako Summit Meeting.

Carlos Castillo-Chavez is a Regents Professor, and Joaquin Bustoz Jr. Professor of Mathematical Biology at Arizona State University and the executive director of the Mathematical and Theoretical Biology Institute and Institute for Strengthening the Understanding of Mathematics and Science at the same university. He has won awards by the American Association for the Advancement of Science (AAAS) Mentor Award and Fellow (2007), the Stanislaw M. Ulam Distinguished Scholar by the Center for Nonlinear Studies at Los Alamos National Laboratory (2003), the Society for Advancement of Chicanos and Native Americans in Science (SACNAS) Distinguished Scientist Award (2001), the Presidential Award for Excellence in Science, Mathematics and Engineering Mentoring (1997), and the Presidential Faculty Fellowship Award from the National Science Foundation and the Office of the President of the United States (1992-1997). Dr. Hsinchun Chen is McClelland Professor of Management Information Systems at the University of Arizona and Andersen Consulting Professor of the Year (1999). He received the B.S. degree from the National Chiao-Tung University in Taiwan, the MBA degree from SUNY Buffalo, and the Ph.D. degree in Information Systems from the New York University. He is author/editor of 10 books and more than 130 SCI journal articles covering intelligence analysis, biomedical informatics, data/text/web mining, digital library, knowledge management, and Web computing. His recent books include: Medical Informatics: Knowledge Management and Data Mining in Biomedicine and Intelligence and Security Informatics for International Security: Information Sharing and Data Mining, both published by Springer. Dr. Chen was ranked #8 in publication productivity in Information Systems (CAIS 2005) and #1 in Digital Library research (IP&M 2005) in two recent bibliometric studies. He serves on ten editorial boards including: ACM Transactions on Information Systems, ACM Journal on Educational Resources