<p>This monograph presents fundamental aspects of modern spectral and other computational methods, which are not generally taught in traditional courses. It emphasizes concepts as errors, convergence, stability, order and efficiency applied to the solution of physical problems. The spectral methods
Introduction to Statistical Methods for Biosurveillance : With an Emphasis on Syndromic Surveillance
โ Scribed by Ronald D. Fricker
- Publisher
- Cambridge University Press
- Year
- 2013
- Tongue
- English
- Leaves
- 418
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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.
โฆ Subjects
Public health surveillance -- Statistical methods. ; Bioterrorism -- Prevention -- Statistical methods. ; Communicable diseases -- Prevention -- Statistical methods.
๐ SIMILAR VOLUMES
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<em>Statistical Methods: An Introduction to Basic Statistical Concepts and Analysis</em>, Second Edition is a textbook designed for students with no prior training in statistics. It provides a solid background of the core statistical concepts taught in most introductory statistics textbooks. Mathema
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