Disease mapping involves the analysis of geo-referenced disease incidence data and has many applications, for example within resource allocation, cluster alarm analysis, and ecological studies. There is a real need amongst public health workers for simpler and more efficient tools for the analysis of geo-referenced disease incidence data. Bayesian and multilevel methods provide the required efficiency, and with the emergence of software packages – such as WinBUGS and MLwiN – are now easy to implement in practice. Provides an introduction to Bayesian and multilevel modelling in disease mapping. Adopts a practical approach, with many detailed worked examples. Includes introductory material on WinBUGS and MLwiN. Discusses three applications in detail – relative risk estimation, focused clustering, and ecological analysis. Suitable for public health workers and epidemiologists with a sound statistical knowledge. Supported by a Website featuring data sets and WinBUGS and MLwiN programs. Disease Mapping with WinBUGS and MLwiN provides a practical introduction to the use of software for disease mapping for researchers, practitioners and graduate students from statistics, public health and epidemiology who analyse disease incidence data.
mapping. Environmetrics, 14:475–490. Lambert, D. (1992). Zero-inflated Poisson regression, with an application to ... Multilevel modelling of the geographical distributions of diseases. ... Disease Mapping with WinBUGS and MLwiN.
The book explores a range of topics in Bayesian inference and
Clayton D, Kaldor J. Empirical Bayes estimates of age-standardized relative risks for use in disease mapping. Biometrics. 1987;43(3):671–81. ... In: Disease mapping with WinBUGS and MLwiN. Chichester: Wiley; 2003a. p. 115–53.
The notation we use follows mostly that of Christensen (1991), as this text most closely links geostatistics to linear model theory. Good texts on geostatistics are Chil`es and Delfiner (2012), Christensen (1991), Cressie (1993), ...
Bayesian spatial analysis. In Handbook of Spatial Analysis, S. Fotheringham and P. Rogerson, eds., Chap. 9. Sage, New York. 16. Lawson, A. B., Browne, W. J., and Vidal- Rodiero, C. L. (2003). Disease Mapping with WinBUGS and MLwiN.
This second edition of Statistical Methods in Spatial Epidemiology is updated and expanded to offer a complete coverage of the analysis and application of spatial statistical methods.
Lawson AB, Browne WJ, Rodeiro CLV (2003) Disease mapping with Win- BUGS and MlwiN. Wiley, New York 9. Lawson AB, Williams FLR (2001) An introductory guide to disease mapping. Wiley, New York 10. Mantel N, Stark CR (1968) Computation of ...
Lawson, A.B., Biggeri, A. and Dreassi, E. (1999) Edge effects in disease mapping. ... Chichester: John Wiley & Sons, Ltd. Lawson, A.B., Browne, W.J. and Vidal-Rodeiro, C.L. (2003) Disease Mapping with WinBUGS and MLwiN.
Environ Health Perspect 112:995–997 Koch T (2005) Cartographies of disease: maps, mapping and medicine. ESRI Press, Redlands Last ... CRC, Boca Raton Lawson AB, Browne WJ, Vidal Rodeiro CL (2003) Disease mapping with WinBUGS and MLwiN.
Bayesian detection of clusters and discontinuities in disease maps. Biometrics 56, 13–21. ... Modelling disease incidence data with spatial and spatio-temporal Dirichlet process mixtures. ... Disease Mapping with WinBUGS and MLwiN.