Making the most of spatial information in health: a tutorial in Bayesian disease mapping for areal data.

Disease maps are effective tools for explaining and predicting patterns of disease outcomes across geographical space, identifying areas of potentially elevated risk, and formulating and validating aetiological hypotheses for a disease. Bayesian models have become a standard approach to disease mapping in recent decades. This article aims to provide a basic understanding of the key concepts involved in Bayesian disease mapping methods for areal data. It is anticipated that this will help in interpretation of published maps, and provide a useful starting point for anyone interested in running disease mapping methods for areal data. The article provides detailed motivation and descriptions on disease mapping methods by explaining the concepts, defining the technical terms, and illustrating the utility of disease mapping for epidemiological research by demonstrating various ways of visualising model outputs using a case study. The target audience includes spatial scientists in health and other fields, policy or decision makers, health geographers, spatial analysts, public health professionals, and epidemiologists.

The role of Macmillan nurse tutors: an interview study with post-holders.

This article explores the role of Macmillan nurse tutors through in-depth, semi-structured tape-recorded interviews with 22 post-holders, focusing on their responsibilities, institutional affiliations and career aspirations. After full transcription, these qualitative data were subjected to open coding. Many tensions and variations within the role were revealed. However, these tutors appeared to be extremely committed to cancer and palliative care. They were concerned about how their future educational position would be maintained in a changing system of health care and health provision.