A0488
Title: Hotspot detection and trend analysis of dengue fever in Taiwan
Authors: Yi-Hung Kung - Fu Jen Catholic University (Taiwan) [presenting]
Abstract: Dengue fever poses a persistent threat to public health in Taiwan. Seasonal outbreaks have become more frequent and severe, often triggered by imported cases and exacerbated by factors such as climate change, urbanization, and increased human mobility. Despite efforts to control the disease, challenges remain in accurately identifying transmission hotspots and predicting outbreak dynamics. The aim is to propose a framework for hotspot detection and trend analysis, combining Kulldorffs likelihood ratio scan statistics with quasi-likelihood methods developed by a prior study, to improve the detection of disease clusters under conditions of spatial confounding and zero-inflated data. By incorporating relevant environmental and socio-economic covariates such as temperature, precipitation, urban density, and mobility, aiming to enhance the accuracy and flexibility of cluster detection while uncovering key risk factors influencing dengue transmission. The proposed methodology not only advances statistical tools for infectious disease mapping but also supports the development of localized early warning systems. This approach provides timely, data-driven insights, enabling more effective allocation of resources and targeted interventions to mitigate future dengue outbreaks in Taiwan.
