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Handbook of Biosurveillance
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Table of Contents

PART I: THE CHALLENGE OF BIOSURVEILLANCE

Chapter 1: Introduction

Chapter 2: Outbreaks and Investigations

Chapter 3: Case Detection, Outbreak Detection, and Outbreak Characterization

Chapter 4: Functional Requirements for Biosurveillance

PART II: ORGANIZATIONS THAT CONDUCT BIOSURVEILLANCE AND THE DATA THEY COLLECT

Chapter 5: Governmental Public Health

Chapter 6: The Healthcare System

Chapter 7: Animal Health

Chapter 8: Laboratories

Chapter 9: Water Suppliers

Chapter 10: Food and Pharmaceutical Industries

Chapter 11: Coroners and Medical Examiners

Chapter 12: Other Organizations That Conduct Biosurveillance

PART III: DATA ANALYSIS

Chapter 13: Case Detection Algorithms

Chapter 14: Classical Time-Series Methods for Biosurveillance

Chapter 15: Combining Multiple Signals for Biosurveillance

Chapter 16: Methods for Detecting Spatial and Spatio-Temporal Clusters

Chapter 17: Natural Language Processing for Biosurveillance

Chapter 18: Bayesian Methods for Diagnosing Outbreaks

Chapter 19: Atmospheric Dispersion Modeling in Biosurveillance

Chapter 20: Methods for Algorithm Evaluation

PART IV: NEWER TYPES OF SURVEILLANCE DATA

Chapter 21: Methods for Evaluating Surveillance Data

Chapter 22: Sales of Over-the-Counter Healthcare Products

Chapter 23: Chief Complaints and ICD Codes

Chapter 24: Absenteeism

Chapter 25: Emergency Call Centers

Chapter 26: The Internet as Sentinel

Chapter 27: Physiologic and Space-Based Sensors

Chapter 28: Data NOS (Not Otherwise Specified)

PART V: DECISION MAKING

Chapter 29: Decision Analysis

Chapter 30: Probabilistic Interpretation of Surveillance Data

Chapter 31: Economic Studies in Biosurveillance

PART VI: BUILDING AND FIELD TESTING BIOSURVEILLANCE SYSTEMS

Chapter 32: Information Technology Standards in Biosurveillance

Chapter 33: Architecture

Chapter 34: Advancing Organizational Integration: Negotiation, Data Use Agreements, Law and Ethics

Chapter 35: Other Design and Implementation Issues

Chapter 36: Project Management

Chapter 37: Methods for Field Testing of Biosurveillance Systems

Epilogue: The Future of Biosurveillance

APPENDICES

CDCâ„¢ Severe Acute Respiratory Syndrome

Sample Questionnaire/Survey

Surveillance Data Tables

Derivation of Bayes’ Rule

Predictive Value Positive and Negative

Data Communication to RODS: Technical Specifications

Data Use Agreement

Department of Health Authorized Use Agreement for Clinical Data

National Retail Data Monitor/RODS Account Access Agreement

Data Security Agreement—Personnel

Data Use Agreement with Commercial Data Provider

Glossary

Index

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A holistic approach to real-time human disease outbreak detection

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