Adaptations for finding irregularly shaped disease clusters.

ABSTRACT:

Background

Recent adaptations of the spatial scan approach to detecting disease clusters have addressed the problem of finding clusters that occur in non-compact and non-circular shapes--such as along roads or river networks. Some of these approaches may have difficulty defining cluster boundaries precisely, and tend to over-fit data with very irregular (and implausible) clusters shapes.

Results & discussion

We describe two simple adaptations to these approaches that can be used to improve the effectiveness of irregular disease cluster detection. The first adaptation penalizes very irregular cluster shapes based on a measure of connectivity (non-connectivity penalty). The second adaptation prevents searches from combining smaller clusters into large super-clusters (depth lim

SUBMITTER: Yiannakoulias N 

PROVIDER: S-EPMC1939838 | biostudies-literature | 2007 Jul

REPOSITORIES: biostudies-literature