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Disease Mapping and Risk Assessment for Public Health
 
 
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Disease Mapping and Risk Assessment for Public Health [Hardcover]

Andrew B. Lawson (Editor), Annibale Biggeri (Editor), Dankmar Böhning (Editor), Emmanuel Lesaffre (Editor), Jean-Fran Viel (Editor), Roberto Bertollini (Editor)

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Book Description

0471986348 978-0471986348 June 22, 1999 1
Offers an in-depth report on advanced statistical tools for public health disease surveillance, which is the result of a prestigious World Health Organisation (WHO) and EU Biomed programme initiative. Traditionally, the role of public health disease surveillance has been to identify and evaluate morbidity and mortality but increasingly, more sophisticated methods are being applied as the authorities extend their studies to include control and prevention of disease. This book brings together leading experts to discuss complex methodologies for the statistical evaluation of disease mapping and risk assessment. It includes a broad variety of statistical techniques and where appropriate, examples are included on topical issues such as the analysis of putative health hazards. For easy reference the text is presented in five distinct sections, each with an introductory review:

* Disease Mapping

* Clustering of Disesase

* Ecological Analysis

* Risk Assessment for Putative Sources of Hazard

* Public Health Applications and Case Studies

Representative of the most pertinent issues within disease surveillance and mapping, this book will provide an accessible overview for statisticians and epidemiologists.

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Editorial Reviews

Review

"…full of rich ideas and methods that are useful..." (Journal of Statistical Computation and Simulation, April 2005)

"...sure to be an essential reference for anyone working in this area" (ISCB Newsletter, December 2000)


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Inside This Book (learn more)
First Sentence:
The representation and analysis of maps of disease incidence data is now established as a basic tool in the analysis of regional public health. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
scotland lip cancer data, ecological regression studies, possible sample locations, ith tract, centroid assignment, leukaemia data, ecological covariates, disease cluster tests, generalised linear mixed models, unstructured heterogeneity, correlated heterogeneity, randomisation tests, true covariate, spatial scan statistic, log relative risks, disease mapping, mixture model approach, hot spot clusters, full posterior distribution, malaria endemicity, public health decision making, ecological bias, risk assessment for public health, marginal posterior distribution, exchangeable model
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, United Kingdom, Department of Health, United States, Lawson University of Aberdeen, West Germany, John Wilev, National Institute of Environmental Health Sciences, Small-Area Variations, Smoking Percent, Sons Lid
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