Conceptual design of an activity-based spatio-temporal data model for SARS transmission analysis

Recently GIS have been used in the surveillance and monitoring of diseases and control of epidemics. Most of those mapping systems use aggregated datasets. This aggregated datasets are not sufficient to support the analysis of epidemiological transmission if the disease is spread mostly person by person from region to region such as SARS Severe acute respiratory syndrome. This paper develops a mobility-oriented spatio-temporal data model to support SARS transmission analysis in a GIS environment by identifying spatial and temporal opportunities for activity participation. The model can support the tracing and predication of spatially varying, temporally dynamic and individually based epidemiological phenomena. A prototype system based on the data model is implemented by a case study based in Hong Kong.