Infectious Disease Informatics

by Chen, Hsinchun; Zeng, Daniel; Yan, Ping

• ISBN13: 9781441912770
• ISBN10: 1441912770
• Edition: 1st
• Format: Hardcover
• Copyright: 2009-11-06
• Publisher: Springer Verlag

Summary

While all the international infectious disease surveillance systems share similar objectives, each system site varies in its system architecture, its information processing management techniques, its algorithms for detection, and each focus on different diseases. INFECTIOUS DISEASE INFORMATICS: Syndromic Surveillance for Public Health and Bio-Defense corrects these problems. The book will analyze and evaluate the outbreak modeling and detection capabilities of the existing surveillance systems from a systematic framework. Specifically, the book will meet the following critical needs in detecting infectious diseases:It will provide an integrated, synthesized, and interdisciplinary analysis of infectious surveillance techniques. It will include statistical modeling techniques, but go beyond statistical modeling to include information systems design, data standards, computational aspects of bio-surveillance, information visualization, and system evaluation. It will emphasize the practical importance of the area and integrate the material from Public Health, Computer Science, Information Systems, Software Engineering, Public Administration Policy, Geographical Information Systems, etc. into a unified state-of-the-art treatment of syndromic surveillance systems. By its very nature, infectious disease surveillance is a dynamic, fast-moving field. Therefore the book will provide policy makers and public health practitioners with the most recent research findings, methodologies, and implementation issues from case studies of concrete application scenarios.

Table of Contents

Preface	p. ix
Author Biographies	p. xiii
Acknowledgments	p. xvii
Syndromic Surveillance Systems
Infectious Disease Informatics: An Introduction and An Analysis Framework	p. 3
Public Health Syndromic Surveillance Systems	p. 9
Summary of Nationwide Syndromic Surveillance Systems	p. 10
Summary of Syndromic Surveillance Systems at the Local, County, and State Levels	p. 17
Summary of Industrial Solutions for Syndromic Surveillance	p. 25
Summary of International Syndromic Surveillance Projects	p. 27
Syndromic Surveillance for Special Events	p. 29
Syndromic Surveillance Data Sources and Collection Strategies	p. 33
Data Sources for Public Health Syndromic Surveillance	p. 33
Comparison of Data Sources	p. 37
Standardized Vocabularies	p. 42
Existing Data Standards Used in Syndromic Surveillance	p. 43
Data Entry and Data Transmission	p. 46
Data Entry Approaches	p. 47
Secure Data Transmission	p. 47
Data Analysis and Outbreak Detection	p. 49
Syndrome Classification	p. 49
Syndrome Classification Approaches	p. 51
Performance of Syndrome Classification Approaches	p. 54
A Taxonomy of Outbreak Detection Methods	p. 55
Retrospective vs. Prospective Syndromic Surveillance	p. 55
Temporal, Spatial, and Spatial-Temporal Outbreak Detection Methods	p. 56
Temporal Data Analysis	p. 61
Statistical Process Control (SPC)-Based Anomaly Detection	p. 61
Serfling Statistic	p. 62
Autoregressive Model-Based Anomaly Detection	p. 63
Hidden Markov Model (HMM)-Based Models	p. 64
Spatial Data Analysis	p. 65
Generalized Linear Mixed Models and Smart Algorithm	p. 66
Spatial Scan Statistic and Its Variations	p. 67
Risk-Adjusted Support Vector Clustering (RSVC) Algorithm	p. 69
Spatial-Temporal Data Analysis	p. 69
Rule-Based Anomaly Detection with Bayesian Network Modeling	p. 69
Population-Wide Anomaly Detection and Assessment (PANDA)	p. 70
Monitoring Multiple Data Streams	p. 70
Special Events Surveillance	p. 71
Summary of Data Analysis Process for Syndromic Surveillance	p. 72
Data Visualization, Information Dissemination, and Alerting	p. 73
Scope and Taxonomy	p. 74
Visual Information Display	p. 74
Visualization of Time-Series Data	p. 75
Visualization of Spatial Information	p. 77
GIS for Disease Event Visualization	p. 79
Spatial-Temporal Disease Modeling and Other Visualization Examples	p. 83
Interactive Visual Data Exploration	p. 84
Summary of Data Visualization in Syndromic Surveillance Applications	p. 85
Information Dissemination and Reporting	p. 86
System Assessment and Evaluation	p. 89
Syndromic Surveillance System Evaluation Framework	p. 90
Evaluation of Outbreak Detection Algorithms	p. 93
Evaluation Methodology	p. 93
Real Data Testing	p. 91
Fully Synthetic Data Testing	p. 92
Semisynthetic Data Testing	p. 94
Evaluation Metrics for Outbreak Detection Algorithms	p. 95
Summary of Representative Evaluation Studies	p. 98
Evaluation of Data Collection and Information Dissemination Components	p. 101
Assessment of Interface Features and System Usability	p. 101
System Usability Evaluation Methodology	p. 101
System Usability Evaluation Metrics	p. 102
Summary of System Usability Evaluation Studies	p. 102
Summary and Discussion	p. 103
Syndromic Surveillance System Case Studies
BioSense	p. 109
BioSense Data Collection and Preprocessing	p. 132
BioSense Data Analysis	p. 113
BioSense Data Visualization, Information Dissemination, and Reporting	p. 114
Case Study: Monitoring Health Effects of Wildfires Using BioSense	p. 116
Further Readings	p. 119
Rods	p. 121
RODS Data Collection	p. 122
RODS Data Analysis	p. 124
RODS Visualization, Information Dissemination, and Reporting	p. 126
Case Study: Syndromic Surveillance with RODS for the 2002 Winter Olympics	p. 128
Further Readings	p. 131
BioPortal	p. 133
BioPortal Data Collection	p. 135
BioPortal Data Analysis	p. 135
BioPortal Visualization, Information Dissemination, and Reporting	p. 136
Case Study: Foot-and-Mouth Disease Situational Awareness	p. 142
Further Readings	p. 144
Essence	p. 147
Essence Data Collection	p. 149
Essence Data Analysis and System Evaluation	p. 150
Essence Interface, Information Dissemination, and Reporting	p. 152
Further Readings	p. 155
New York City Syndromic Surveillance Systems	p. 157
NYC ED Syndromic Surveillance System Data Collection	p. 158
NYC ED Syndromic Surveillance System Data Analysis and Field Investigations	p. 159
NYC ED Syndromic Surveillance System Visualization, Information Dissemination, and Reporting	p. 360
Case Study: Respiratory Illness Surveillance Using Multiple Syndromic Systems in New York City	p. 162
Further Readings	p. 164
Ears	p. 167
Ears Data Collection and Data Preprocessing	p. 168
Key Ears Aberration Detection Methods	p. 169
Ears Visualization, Information Dissemination, and Reporting	p. 171
Case Study: PostHurricane Public Health Surveillance with EARS.	p. 173
Further Readings	p. 174
Argus	p. 177
Health Map	p. 183
Challenges and Future Directions	p. 187
Challenges for Syndromic Surveillance Research	p. 187
Summary and Future Directions	p. 188
References	p. 191
Subject Index	p. 207
Table of Contents provided by Ingram. All Rights Reserved.