Disease Mapping with WinBUGS and MLwiN

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. <ul> <li>Provides an introduction to Bayesian and multilevel modelling in disease mapping.</li> <li>Adopts a practical approach, with many detailed worked examples.</li> <li>Includes introductory material on WinBUGS and MLwiN.</li> <li>Discusses three applications in detail – relative risk estimation, focused clustering, and ecological analysis.</li> <li>Suitable for public health workers and epidemiologists with a sound statistical knowledge.</li> <li>Supported by a Website featuring data sets and WinBUGS and MLwiN programs.</li> </ul> <p><i>Disease Mapping with WinBUGS and MLwiN</i>  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.</p>