
doi: 10.1002/sim.933
pmid: 11439429
AbstractThe analysis of the geographical distribution of disease incidence or prevalence is now of considerable importance for public health workers and epidemiologists alike. Important disease variations often have a spatial expression and so spatial analysis methods are an important additional tool in this connection. In this tutorial I have aimed to highlight the main issues relating to the analysis of disease where the goal is the reduction in noise in a disease map. This area is sometimes simply called disease mapping. A number of modelling approaches to disease mapping are considered and a case study highlighting the methods advocated is also included. Copyright © 2001 John Wiley & Sons, Ltd.
Risk, Likelihood Functions, Biometry, Bayes Theorem, Models, Biological, Respiratory Tract Neoplasms, United Kingdom, Cluster Analysis, Humans, Epidemiologic Methods, Laryngeal Neoplasms
Risk, Likelihood Functions, Biometry, Bayes Theorem, Models, Biological, Respiratory Tract Neoplasms, United Kingdom, Cluster Analysis, Humans, Epidemiologic Methods, Laryngeal Neoplasms
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