Flexible-Elliptical Spatial Scan Method

The detection of disease clusters in spatial data analysis plays a crucial role in public health, while the circular scan method is widely utilized for this purpose, accurately identifying non-circular (irregular) clusters remains challenging and reduces detection accuracy. To overcome this limitation, various extensions have been proposed to effectively detect arbitrarily shaped clusters. In this paper, we combine the strengths of two well-known methods, the flexible and elliptic scan methods, which are specifically designed for detecting irregularly shaped clusters. We leverage the unique characteristics of these methods to create candidate zones capable of accurately detecting irregularly shaped clusters, along with a modified likelihood ratio test statistic. By inheriting the advantages of the flexible and elliptic methods, our proposed approach represents a practical addition to the existing repertoire of spatial data analysis techniques.

Automated summary

The detection of disease clusters in spatial data analysis is important in public health. While the circular scan method is commonly used, accurately identifying non-circular (irregular) clusters remains challenging. We propose a method that combines the strengths of the flexible and elliptic scan methods to accurately detect irregularly shaped clusters.