Introduction to Statistical Methods for Biosurveillance: With an Emphasis on Syndromic Surveillance

by Ronald D. Fricker

Overview

Bioterrorism is not a new threat, but in an increasingly interconnected world, the potential for catastrophic outcomes is greater today than ever. The medical and public health communities are establishing biosurveillance systems designed to proactively monitor populations for possible disease outbreaks as a first line of defense. The ideal biosurveillance system should identify trends not visible to individual physicians and clinicians in near-real time. Many of these systems use statistical algorithms to look for anomalies and to trigger epidemiologic investigation, quantification, localization, and outbreak management. This book discusses the design and evaluation of statistical methods for effective biosurveillance for readers with minimal statistical training. Weaving public health and statistics together, it presents basic and more advanced methods, with a focus on empirically demonstrating added value. Although the emphasis is on epidemiologic and syndromic surveillance, the statistical methods can be applied to a broad class of public health surveillance problems.

Product Details

ISBN-13:	9780521191340
Publisher:	Cambridge University Press
Publication date:	02/25/2013
Pages:	411
Product dimensions:	6.38(w) x 9.53(h) x 1.02(d)

About the Author

Ronald D. Fricker, Jr is an Associate Professor of Operations Research and the Associate Chair for Research at the Naval Postgraduate School (NPS). Prior to joining NPS, Dr Fricker was a Senior Statistician at the RAND Corporation and the Associate Director of the National Security Research Division. Published widely in leading professional journals, he is a Fellow of the American Statistical Association, an Elected Member of the International Statistical Institute, and a former chair of the ASA Section on Statistics in Defense and National Security. He is a contributing editor to Interfaces and is on the editorial boards of Statistics, Politics, and Policy and the International Journal of Quality Engineering and Technology. Fricker's current research is focused on studying the performance of various statistical methods for use in biosurveillance, particularly syndromic surveillance, and statistical process control methodologies more generally.

Table of Contents

Part I. Introduction to Biosurveillance: 1. Overview; 2. Biosurveillance data; Part II. Situational Awareness: 3. Situational awareness for biosurveillance; 4. Descriptive statistics for displaying the situation; 5. Statistical models for evaluating the situation; Part III. Early Event Detection: 6. Design and performance evaluation; 7. Univariate temporal methods; 8. Multivariate temporal methods; 9. Spatio-temporal methods; Part IV. Putting It All Together: 10. Simulating biosurveillance data; 11. Applying the temporal methods to real data; 12. Comparing methods to better understand and improve; 13. Frontiers, open questions, and future research.

Editorial Reviews

Reviewer: Hemang B Panchal, MD, MPH (East Tennessee State University Quillen College of Medicine)
Description: This book focuses on design and evaluation of basic and advanced statistical methods for biosurveillance with an emphasis on syndromic surveillance, which can help in early detection of bioterrorism. The author has well rounded statistical and research experience especially in the area of defense and national security.
Purpose: The purpose is to introduce the statistical tools for evaluation of various methods of biosurveillance. This book would help users in comparing biosurveillance systems and identifying statistically better biosurveillance systems for early detection of bioterrorism.
Audience: The intended audience includes students in advanced undergraduate and graduate biostatistics courses, researchers and statisticians working for public health departments, national security departments, defense departments, or in the specialty areas of infectious diseases or bioterrorism.
Features: The first two parts provide an overview of biosurveillance problems and data, an introduction to situational awareness, and a foundation in statistical tools and models useful for perception and projection of situational awareness that includes time series and regression-based models. Part III emphasizes early event detection design and performance metrics and describes statistical methods used for early event detection. Part IV puts it all together with real data examples of the application of early event detection methods followed by applications for bioterrorism surveillance with simulation of data sets. The final part is an appendix section that provides a brief review of probability, random variables, and sampling distributions and discusses methods for simulating biosurveillance data. Each chapter in these parts contains an additional reading section.
Assessment: This is excellent overview of basic statistical methods for biosurveillance that also provides updates and references for advanced statistical methods. It is strongly recommended to beginning researchers and statisticians who are interested in biosurveillance.

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