Spatial statistical methods in health.
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.
Bailey
T C
TC
School of Mathematical Sciences, University of Exeter, Exeter, UK.
D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D011634:Public Health