Spatial and syndromic surveillance for public health

Following the events of 9/11 and in the current world climate, there is increasing concern of the impact of potential bioterrorism attacks. Spatial surveillance systems are used to detect changes in public health data, and alert us to possible outbreaks of disease, either from natural resources or f...

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Bibliographic Details
Corporate Authors: John Wiley & Sons.
Group Author: Lawson, Andrew (Andrew B.); Kleinman, Ken
Published:
Literature type: Electronic eBook
Language: English
Subjects:
Online Access: http://onlinelibrary.wiley.com/book/10.1002/0470092505
Summary: Following the events of 9/11 and in the current world climate, there is increasing concern of the impact of potential bioterrorism attacks. Spatial surveillance systems are used to detect changes in public health data, and alert us to possible outbreaks of disease, either from natural resources or from bioterrorism attacks.
Carrier Form: 1 online resource (xiv, 269 pages) : illustrations
Bibliography: Includes bibliographical references and index.
ISBN: 0470092483
9780470092484
0470092505
9780470092507
9780470092491
0470092491
Index Number: RA652
CLC: R1
Contents: Introduction : spatial and syndromic surveillance for public health / Andrew B. Lawson and Ken Kleinman -- Overview of temporal surveillance / Yann Le Strat -- Optimal surveillance / Marianne Frisén and Christian Sonesson -- Spatial and spatio-temporal disease analysis / Andrew B. Lawson -- Generalized linear models and generalized linear mixed models for small-area surveillance / Ken Kleinman -- Spatial surveillance and cumulative sum methods / Peter A. Rogerson -- Scan statistics for geographical disease surveillance : an overview / Martin Kulldorff -- Distance-based methods for spatial and spatio-temporal surveillance / Laura Forsberg [and others] -- Multivariate surveillance / Christian Sonesson and Marianne Frisén -- Bayesian network approaches to detection / Weng-Keen Wong and Andrew W. Moore -- Efficient scan statistic computations / Daniel B. Neill and Andrew W. Moore -- Bayesian data mining for health surveillance / David Madigan -- Advanced modeling for surveillance : clustering of relative risk changes / Andrew B. Lawson.