Methods of Mapping and Identifying Small Clusters of Rare Diseases with Applications to Geographical Epidemiology

Geographical variation operates at a variety of scales. Methods of mapping variation in disease incidence between different countries or even counties are relatively well developed. When, however, the question relates to much smaller aggregations (that is, “clustering”), attention has mainly been restricted to areas near putative point hazards; the majority of cases are excluded from such an investigation. In this study we show how clustering may be investigated and displayed in such a way that it becomes a powerful tool in epidemiological research. As examples we use incidence data from the Yorkshire health region for selected childhood cancers and adult haematopoietic malignancies. The methods would readily extend to any small clusters of rare events.     

Electoral inequalities in the 1990 federal elections

Due to the concentration of Australian Labor Party voters, that party has to poll more votes than the Liberal and National Parties to win an election. That is not a gerrymander, for no matter how fairly the boundaries were drawn, Labor would still need to poll more votes than its opponents under the preferential, single‐member constituency voting system. Nevertheless, even under perfectly fair electoral redistributions, Labor is bound to come off worst because Labor voters are more highly concentrated than non‐Labor voters.