Bayesian methods for mapping disease risk

Abstract

The construction of disease maps has been a central problem of descriptive epidemiology throughout its history. There are two main classes of disease maps: maps of standardized rates, and maps of statistical significance of the difference between risk in each area and the overall risk averaged over the entire map. This chapter focuses on the mapping problem with particular attention to smoothing maps of rates computed for small areas. The use of spatial correlation structure along with Bayesian concepts suggests ways of smoothing these maps.

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