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Spatial Analysis in Epidemiology$
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Dirk U. Pfeiffer, Timothy P. Robinson, Mark Stevenson, Kim B. Stevens, David J. Rogers, and Archie C. A. Clements

Print publication date: 2008

Print ISBN-13: 9780198509882

Published to Oxford Scholarship Online: September 2008

DOI: 10.1093/acprof:oso/9780198509882.001.0001

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Spatial variation in risk

Spatial variation in risk

Chapter:
(p.67) CHAPTER 6 Spatial variation in risk
Source:
Spatial Analysis in Epidemiology
Author(s):

Dirk U. Pfeiffer

Timothy P. Robinson

Mark Stevenson

Kim B. Stevens

David J. Rogers

Archie C. A. Clements

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198509882.003.0006

This chapter discusses spatial variation in risk. Epidemiological disease investigations should include an assessment of the spatial variation of disease risk, as this may provide important clues leading to causal explanations. The objective is to produce a map representation of the important spatial effects present in the data while simultaneously removing any distracting noise or extreme values. The resulting smoothed map should have increased precision without introducing significant bias. The method used to analyse the data depends on how they have been recorded. Smoothing based on kernel functions, smoothing based and on Bayesian models, and spatial interpolation are discussed.

Keywords:   spatial variations, spatial epidemiological analysis, map representation, spatial effects, smoothing, kernel functions, Bayesian models, spatial interpolation

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