A0843
Title: A functional generalized additive model-based scan statistic for disease cluster detection
Authors: Michio Yamamoto - Osaka University / RIKEN AIP (Japan) [presenting]
Tatsuhiko Anzai - Tokyo Medical and Dental University (Japan)
Kunihiko Takahashi - Tokyo Medical and Dental University (Japan)
Abstract: Detecting spatial clusters of diseases is crucial for understanding disease patterns and developing effective prevention and treatment strategies. Spatial scan statistics are powerful methods for detecting spatial clusters with a variable scanning window size. A new spatial scan statistic is proposed that considers the spatial correlation of an outcome variable and handles multiple functional covariates that indicate past information over time. Specifically, the proposed method flexibly models these factors using the framework of functional generalized additive models. The performance of the proposed approach will be examined through a simulation study and real data analysis.
