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Spatial statistical methods in health

Overview of attention for article published in Cadernos de Saúde Pública, September 2002
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Title
Spatial statistical methods in health
Published in
Cadernos de Saúde Pública, September 2002
DOI 10.1590/s0102-311x2001000500011
Pubmed ID
Authors

Trevor C. Bailey

Abstract

The study of the geographical distribution of disease incidence and its relationship to potential risk factors (referred to here as "geographical epidemiology") has provided, and continues to provide, rich ground for the application and development of statistical methods and models. In recent years increasingly powerful and versatile statistical tools have been developed in this application area. This paper discusses the general classes of problem in geographical epidemiology and reviews the key statistical methods now being employed in each of the application areas identified. The paper does not attempt to exhaustively cover all possible methods and models, but extensive references are provided to further details and to additional approaches. The overall aim is to provide a picture of the "current state of the art" in the use of spatial statistical methods in epidemiological and public health research. Following the review of methods, the main software environments which are available to implement such methods are discussed. The paper concludes with some brief general reflections on the epidemiological and public health implications of the use of spatial statistical methods in health and on associated benefits and problems.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 126 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 5 4%
France 2 2%
Italy 1 <1%
Kenya 1 <1%
Czechia 1 <1%
Unknown 116 92%

Demographic breakdown

Readers by professional status Count As %
Student > Master 20 16%
Student > Ph. D. Student 16 13%
Researcher 14 11%
Student > Doctoral Student 12 10%
Student > Bachelor 11 9%
Other 37 29%
Unknown 16 13%
Readers by discipline Count As %
Environmental Science 17 13%
Medicine and Dentistry 17 13%
Agricultural and Biological Sciences 11 9%
Earth and Planetary Sciences 10 8%
Mathematics 9 7%
Other 42 33%
Unknown 20 16%