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Spatial epidemiology: methods and applications
  1. Sarah Scobie
  1. Commission for Health Improvement, UKJECHJ Epidemiol Community

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    P Elliot, J C Wakefield, N G Best, D J Briggs. (Pp 475; £32.50). Oxford University Press, 2001.

    I came to review this book by chance, having studied spatial epidemiology some years ago. Reviewing the book was an opportunity to update myself in this field, and see what had changed and what was new.

    The book covers a wide range of material, including a description of data sources and their limitations, and the theoretical basis for the statistical methods that can be used. The second half of the book is divided between two types of application: disease mapping and clustering studies, and studies of exposure to environmental health risks. There are detailed descriptions of the use of statistical methods and models, and examples, some graphical, of the results of the analyses. The authors take a historical perspective, so that throughout the book there is a sense of how the methods have developed and of the direction of future work.

    Some sections of the book would be accessible to a wide readership—I found myself more comfortable with the material on data sources and the chapters on disease mapping, where the results, if not the methods, are intuitively easy to understand. Many of the chapters will only be of value to specialists in this field, in part because of the statistical methods used, and in part because the methods are comparatively new and interpretation of the results complex. For the less expert reader, the two sections on applications would benefit from a concluding chapter, to help the reader fit together the different methods that have been described.

    What do I conclude about the state of spatial epidemiology? Limitations of data sources remain a constraint. The trend for closer working between people from different disciplines has continued, although the joints within in the book demonstrate that there is more progress to be made here. The development of new statistical techniques and the increase in computing power is apparent, although there is some way to go in the routine application of these techniques.