Introduction to Statistical Methods for Biosurveillance
eBook - PDF

Introduction to Statistical Methods for Biosurveillance

With an Emphasis on Syndromic Surveillance

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Introduction to Statistical Methods for Biosurveillance

With an Emphasis on Syndromic Surveillance

About this book

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.

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Yes, you can access Introduction to Statistical Methods for Biosurveillance by Ronald D. Fricker in PDF and/or ePUB format, as well as other popular books in Medicine & Biostatistics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Contents
  2. Preface
  3. Acknowledgments
  4. I Introduction to Biosurveillance
  5. 2 Biosurveillance Data
  6. II Situational Awareness
  7. 4 Descriptive Statistics for Comprehending the Situation
  8. 5 Statistical Models for Projecting the Situation
  9. III Early Event Detection
  10. 7 Univariate Temporal Methods
  11. 8 Multivariate Temporal and Spatio-temporal Methods
  12. IV Putting It All Together
  13. 10 Comparing Methods to Understand and Improve Biosurveillance Performance
  14. V Appendices
  15. B Appendix B: Simulating Biosurveillance Data
  16. C Tables
  17. References