Literature DB >> 11439429

Disease map reconstruction.

A B Lawson1.   

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. Copyright 2001 John Wiley & Sons, Ltd.

Mesh:

Year:  2001        PMID: 11439429     DOI: 10.1002/sim.933

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  16 in total

1.  Geographical epidemiology, spatial analysis and geographical information systems: a multidisciplinary glossary.

Authors:  Mohsen Rezaeian; Graham Dunn; Selwyn St Leger; Louis Appleby
Journal:  J Epidemiol Community Health       Date:  2007-02       Impact factor: 3.710

2.  Exploring scale-dependent correlations between cancer mortality rates using factorial kriging and population-weighted semivariograms.

Authors:  Pierre Goovaerts; Geoffrey M Jacquez; Dunrie Greiling
Journal:  Geogr Anal       Date:  2005-04

3.  The ecological association between suicide rates and indices of deprivation in English local authorities.

Authors:  Mohsen Rezaeian; Graham Dunn; Selwyn St Leger; Louis Appleby
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2005-09-22       Impact factor: 4.328

4.  Combining area-based and individual-level data in the geostatistical mapping of late-stage cancer incidence.

Authors:  Pierre Goovaerts
Journal:  Spat Spatiotemporal Epidemiol       Date:  2009 Oct-Dec

5.  Neighborhood size and local geographic variation of health and social determinants.

Authors:  Mohammad Ali; Jin-Kyung Park; Vu Dinh Thiem; Do Gia Canh; Michael Emch; John D Clemens
Journal:  Int J Health Geogr       Date:  2005-06-01       Impact factor: 3.918

6.  Geostatistical analysis of disease data: estimation of cancer mortality risk from empirical frequencies using Poisson kriging.

Authors:  Pierre Goovaerts
Journal:  Int J Health Geogr       Date:  2005-12-14       Impact factor: 3.918

7.  Application of Poisson kriging to the mapping of cholera and dysentery incidence in an endemic area of Bangladesh.

Authors:  Mohammad Ali; Pierre Goovaerts; Nushrat Nazia; M Zahirul Haq; Mohammad Yunus; Michael Emch
Journal:  Int J Health Geogr       Date:  2006-10-13       Impact factor: 3.918

8.  Spatial patterns of natural hazards mortality in the United States.

Authors:  Kevin A Borden; Susan L Cutter
Journal:  Int J Health Geogr       Date:  2008-12-17       Impact factor: 3.918

9.  Spatial risk for gender-specific adult mortality in an area of southern China.

Authors:  Mohammad Ali; Yang Jin; Deok Ryun Kim; Zhou Bao De; Jin Kyung Park; Rion Leon Ochiai; Baiqing Dong; John D Clemens; Camilo J Acosta
Journal:  Int J Health Geogr       Date:  2007-07-24       Impact factor: 3.918

10.  Exploratory disease mapping: kriging the spatial risk function from regional count data.

Authors:  Olaf Berke
Journal:  Int J Health Geogr       Date:  2004-08-26       Impact factor: 3.918

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