Identification of geographic clusters for temporal heterogeneity with application to dengue surveillance.

ABSTRACT: Identifying transmission of hot spots with temporal trends is important for reducing infectious disease propagation. Cluster analysis is a particularly useful tool to explore underlying stochastic processes between observations by grouping items into categories by their similarity. In a study of epidemic propagation, clustering geographic regions that have similar time series could help researchers track diffusion routes from a common source of an infectious disease. In this article, we propose a two-stage scan statistic to classify regions into various geographic clusters by their temporal heterogeneity. The proposed scan statistic is more flexible than traditional methods in that contiguous and nonproximate regions with similar temporal patterns can be identified simultaneously. A simula

SUBMITTER: Lin PS 

PROVIDER: S-EPMC9298438 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature