American Journal of Epidemiology Vol. 154, No. 9 : 881-882
Copyright © 2001 by The Johns Hopkins University School of Hygiene and Public Health
BOOK REVIEWS |
An Introductory Guide to Disease Mapping
Environmental Health Investigations Branch Division of Environmental and Occupational Disease Control California Department of Health Services Oakland, CA 94612
In the last decade, we have seen an explosion of interest in disease mapping, with the recent developments in advanced spatial statistics and the increasing availability of computerized geographic information system technology. Geographic clustering of childhood leukemia cases has become an issue of concern to the general public, from the clusters investigated near the Sellafield nuclear facility in the United Kingdom to the Woburn, Massachusetts, investigation popularized by the film "A Civil Action." The new volume on disease mapping by Lawson and Williams (1
) may be of interest to epidemiologists who would like to read a textbook that gives a broad overview of the issues involved but is short on specifics.
The book begins with a brief history of disease mapping, including the requisite illustration of John Snow's mapping of cholera deaths in London, followed by a discussion of modern developments such as the construction of disease atlases. Unfortunately for US readers, the examples of atlases and other data resources given here and elsewhere in the book only refer to UK sources–omitting mention, for example, of the fine Atlas of Cancer Mortality in the United States (2), which was commissioned by the National Cancer Institute. Subsequent chapters deal with the visual construction of maps, data sources for maps, study design issues, and basic and advanced methods.
The chapter on basic methods in examining geographic disease variation discusses standardization of rates, calculating expected rates, and the use of covariates such as deprivation indices for geographic analysis. To the authors' credit, the chapter includes a section on mapping the amount of variability in the data. Too often, estimates of rates are mapped with the viewer being kept in the dark as to the magnitude of the standard errors underlying each rate. This is particularly a problem in the interpretation of rates for areas with small populations. However, one of the most common approaches in dealing with this issue–the use of empirical Bayes estimation (3), which shrinks the most unstable estimates towards the population mean–is neglected in the authors' analysis.
In the chapter on advanced methods, the authors discuss smoothing of rates using density estimation and modeling approaches for count data. Regrettably, in the illustration of density estimation, no references are provided for the reader who wishes to further explore how to execute this method. Disease clustering is a complicated subject, and it is often a challenge for public health epidemiologists to properly explain its significance to the affected communities. Although the authors do a fine job of introducing the concepts of cluster definitions, hypothesis tests, and modeling issues, this section could have benefitted from a more general discussion of the utility of searching for cluster "hot spots" and some of the limitations of these investigations, especially investigations into non-infectious-disease clusters. To detect a significant association between an environmental exposure and clustering of disease, the magnitude of the association must be large, and the purported exposure should be pervasive in the community (4). A discussion of issues such as disease specificity, confounding, exposure-illness lag time, and the role of chance in searching for clusters would also have been appropriate here.
The text gives short shrift to a discussion of confidentiality issues pertaining to the mapping of health data. This is especially unfortunate in light of the fact that this may be the greatest obstacle limiting our ability to map disease and that methods dealing with confidentiality concerns have been developed to mask the locations of illness (5). Similarly, although the advent of modern geographic information systems has played a major role in the development of disease mapping, the book devotes less than one page to this important topic (in the appendix).
The final chapter is devoted to public health surveillance and mapping, with a discussion of mapping differences in rates. Although the authors had previously recommended mapping the variability of rates, this chapter doesn't adequately highlight the problem of the law of small numbers—the fact that the variability in rates increases as the size of the population decreases. To avoid this problem, methods of smoothing recommended in the advanced methods chapter should be utilized.
While Lawson and Williams provide some adequate introductory material on the subject of disease mapping, epidemiologists looking for a more definitive understanding would do better by reading the classic treatment of the subject in Haggett and Cliff's Atlas of Disease Distributions (6). There has yet to be a better textbook published that illustrates the utility of disease mapping for epidemiologic research.
NOTES
By A. B. Lawson and F. L. R. Williams
ISBN 0-471-86059-X, John Wiley and Sons, Inc., New York, New York (Telephone: 800-225-5945, Fax: 732-302-2300, World Wide Web: www.wiley.com, E-mail: bookinfo{at}wiley.com), 2001, 142 pp., Hardcover $75.00
REFERENCES
- Lawson AB, Williams FL. An introductory guide to disease mapping. New York, NY: John Wiley and Sons, Inc, 2001.
- 2.National Cancer Institute. Atlas of cancer mortality in the United States, 1950–94. Bethesda, MD: Cancer Information Service, National Cancer Institute, 1999. (NCI publication no. T012).
- 3.Clayton D, Kaldor J. Empirical Bayes estimates of age-standardized relative risk for use in disease mapping. Biometrics 1987;43:671–81.[Web of Science][Medline]
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4.Neutra RR. Counterpoint from a cluster buster. Am J Epidemiol 1990;132:1–8.
[Free Full Text] - 5.Armstrong MP, Rushton G, Zimmerman DL. Geographically masking health data to preserve confidentiality. Stat Med 1999;18:497–525.[Web of Science][Medline]
- 6.Haggett P, Cliff AD. Atlas of disease distributions: analytic approaches to epidemiological data. Oxford, United Kingdom: Basil Blackwell Ltd, 1988.
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