Optimizing the maximum reported cluster size in the spatial scan statistic for survival data.

ABSTRACT:

Background

The spatial scan statistic is a useful tool for cluster detection analysis in geographical disease surveillance. The method requires users to specify the maximum scanning window size or the maximum reported cluster size (MRCS), which is often set to 50% of the total population. It is important to optimize the maximum reported cluster size, keeping the maximum scanning window size at as large as 50% of the total population, to obtain valid and meaningful results.

Results

We developed a measure, a Gini coefficient, to optimize the maximum reported cluster size for the exponential-based spatial scan statistic. The simulation study showed that the proposed method mostly selected the optimal MRCS, similar to the true cluster size. The detection accuracy was higher for

SUBMITTER: Lee S 

PROVIDER: S-EPMC8265152 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature