Spatial Epidemiology Short Course: Bibliography
Further Reading
Elliott, P, Wakefield, JC, Best, NG and Briggs, D. eds. (2000). Spatial Epidemiology: Methods and
Applications. Oxford University Press, Oxford.
Gilks, W.R., Richardson, S. and Spiegelhalter, D.J. (1996). Markov Chain Monte Carlo in Practice,
Chapman and Hall, New York.
Journal of the Royal Statistical Society, Series A. (2001). 164 (1). Special issue on the analysis and
interpretation of disease clusters and ecological studies.
Wakefield, J.C. and Elliott, P. (1999). Issues in the statistical analysis of small-area health data. Statistics in
Medicine, 18, 2377-99.
Clustering and Point Source Studies
Alexander, F. and Boyle, P. (1996). Methods for investigating localized clustering of disease. IARC
Scientific Publications 135 International Agency for Reseach on Cancer, Lyon.
Besag, J. and Newell, J. (1991). The detection of clusters in rare diseases. Journal of the Royal Statistical
Society, Series A, 154, 143-55.
Bithell, J.F. and Stone, R.A. (1989). On statistical methods for analysing the geographical distribution of
cancer cases near nuclear installations. Journal of Epidemiology and Community Health, 43, 79-85.
Cuzick, J. and Edwards, R. (1990). Spatial clustering for inhomogeneous populations. Journal of the Royal
Statistical Society, Series B, 52, 73-104.
Hills, M. and Alexander, F. (1989). Statistical methods used in assessing the risk of disease near a source of
possible environmental pollution: a review. Journal of the Royal Statistical Society, Series A, 152 (3).
Moran, P. (1948). The interpretation of statistical maps. Journal of the Royal Statistical Society, Series B,
10, 243-51.
Pothoff, R.F. and Whittinghill, M. (1966). Testing for homogeneity in the Poisson distribution. Biometrika,
53, 183-90.
Stone, R.A. (1988). Investigations of excess environmental risks around putative sources: Statistical
problems and a proposed test. Statistics in Medicine, 7, 649-60.
Tango, T. (1995). A class of tests for detecting ‘general’ and ‘focused’ clustering of rare diseases. Statistics
in Medicine, 14, 2323-5.
Disease Mapping, Ecological Regression and Spatial Modelling
Armstrong, B.G. (1998). Effect of measurement error on epidemiological studies of environmental and
occupational exposures. Occupational and Environmental Medicine, 55, 651-6.
Best, N.G. and Wakefield, J.C. (1999). “Accounting for inaccuracies in population counts and case
registration in cancer mapping studies”, Journal of the Royal Statistical Society, Series A,162, 363-82.
Besag, J., York, J. and Mollie, A. (1991). Bayesian image restoration, with two applications in spatial
statistics, Ann. Inst. Statist. Math., 43, 1-59.
Clayton, D.G. and Kaldor, J. (1987). Empirical Bayes estimates of age-standardized relative risks for use in
disease mapping, Biometrics}, 43, 671-81.
Cliff, A.D. and Ord, J.K. (1981). Spatial processes: models and applications, Pion, London.
Cressie, N.A. and Chan, N.H. (1989). Spatial modeling of regional variables, Journal of the American
Statistical Association, 84, 393-401.
Knorr-Held, L. and Besag, J. (1998). Modelling risk from a disease in time and space. Statistics in Medicine,
17, 2045-60.
Pascutto, C., Wakefield, J.C., Best, N.G., Richardson, S., Bernardinelli, L., Staines, A. and Elliott, P. (2000).
Statistical issues in the analysis of disease mapping data, Statistics in Medicine, 19, 2593-19.