Modeling Spatial Heterogeneity with Excess Zeroes from School Absenteeism dSata

Absenteeism has been considered as a potential indicator for the early detection of infectious disease outbreaks in population, especially in primary schools. However, in practice this data are often characterized by an excess of zeros and spatial heterogeneity. In a project on integrated syndromic surveillance system (ISSC) in rural China, Random effect zero-inflated Poisson (RE-ZIP) model was applied to simultaneously quantify the spatial heterogeneity for “occurrence” and “intensity” on school absenteeism data.

Objective

To describe and explore the spatial heterogeneity via Random effects zero-inflated Poisson model (RE-ZIP) for absenteeism surveillance in primary school for early detection of infectious disease outbreak in rural China.