Literature DB >> 10997205

Spatial statistics and geographical information systems in epidemiology and public health.

T P Robinson1.   

Abstract

This chapter surveys the principles behind spatial statistics and geographic information systems (GIS), and their application to epidemiology and public health. Like the other introductory chapters, it is aimed mainly to facilitate understanding in the chapters specific to certain diseases that follow, and to provide a short introduction to the field. A brief overview of spatial statistics and GIS is provided in the introduction. The sections that follow explore the ways in which we can map the distribution of disease, ways in which we can look for spatial patterns in the distribution of disease, and ways in which we can apply spatial statistics and GIS to the problem of identifying the causal factors of observed patterns. In the last section I discuss some of the ways in which these techniques have been applied to assist decision making for disease intervention, and conclude by discussing future developments in the field, and some of the issues surrounding the integration of spatial statistics and GIS.

Mesh:

Year:  2000        PMID: 10997205     DOI: 10.1016/s0065-308x(00)47007-7

Source DB:  PubMed          Journal:  Adv Parasitol        ISSN: 0065-308X            Impact factor:   3.870


  17 in total

1.  GIS and multiple-criteria evaluation for the optimisation of tsetse fly eradication programmes.

Authors:  Elias Symeonakis; Tim Robinson; Nick Drake
Journal:  Environ Monit Assess       Date:  2006-10-21       Impact factor: 2.513

2.  Remote sensing, geographical information system and spatial analysis for schistosomiasis epidemiology and ecology in Africa.

Authors:  C Simoonga; J Utzinger; S Brooker; P Vounatsou; C C Appleton; A S Stensgaard; A Olsen; T K Kristensen
Journal:  Parasitology       Date:  2009-07-23       Impact factor: 3.234

3.  Spatial distribution and enteroparasite contamination in peridomiciliar soil and water in the Apucaraninha Indigenous Land, southern Brazil.

Authors:  Joseane Balan da Silva; Camila Piva; Ana Lúcia Falavigna-Guilherme; Diogo Francisco Rossoni; Max Jean de Ornelas Toledo
Journal:  Environ Monit Assess       Date:  2016-03-09       Impact factor: 2.513

Review 4.  The applications of model-based geostatistics in helminth epidemiology and control.

Authors:  Ricardo J Soares Magalhães; Archie C A Clements; Anand P Patil; Peter W Gething; Simon Brooker
Journal:  Adv Parasitol       Date:  2011       Impact factor: 3.870

5.  Geomatics in injury prevention: the science, the potential and the limitations.

Authors:  M D Cusimano; M Chipman; R H Glazier; C Rinner; S P Marshall
Journal:  Inj Prev       Date:  2007-02       Impact factor: 2.399

6.  Upscale or downscale: applications of fine scale remotely sensed data to Chagas disease in Argentina and schistosomiasis in Kenya.

Authors:  Uriel Kitron; Julie A Clennon; M Carla Cecere; Ricardo E Gürtler; Charles H King; Gonzalo Vazquez-Prokopec
Journal:  Geospat Health       Date:  2006-11       Impact factor: 1.212

Review 7.  Large-scale spatial population databases in infectious disease research.

Authors:  Catherine Linard; Andrew J Tatem
Journal:  Int J Health Geogr       Date:  2012-03-20       Impact factor: 3.918

8.  Using geographical information systems mapping to identify areas presenting high risk for traumatic brain injury.

Authors:  Angela Colantonio; Byron Moldofsky; Michael Escobar; Lee Vernich; Mary Chipman; Barry McLellan
Journal:  Emerg Themes Epidemiol       Date:  2011-11-04

Review 9.  Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control.

Authors:  Simon Brooker
Journal:  Trans R Soc Trop Med Hyg       Date:  2006-10-20       Impact factor: 2.184

10.  Defining equity in physical access to clinical services using geographical information systems as part of malaria planning and monitoring in Kenya.

Authors:  A M Noor; D Zurovac; S I Hay; S A Ochola; R W Snow
Journal:  Trop Med Int Health       Date:  2003-10       Impact factor: 2.622

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