title: Disease map reconstruction.
abstract: The 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.
authors: Department of Mathematical Sciences, University of Aberdeen, Aberdeem, UK.
authors: A B
authors: AB
authors: Lawson
mesh_terms: D001499:Bayes Theorem; D001699:Biometry; D016000:Cluster Analysis; D004812:Epidemiologic Methods; D006801:Humans; D007822:Laryngeal Neoplasms / Q000453:epidemiology; D016013:Likelihood Functions; D008954:Models, Biological; D012142:Respiratory Tract Neoplasms / Q000453:epidemiology; D012306:Risk; D006113:United Kingdom