In view of the growing human health concern as the avian flu outbreaks spread the entire world, a timely active protection system will be crucial to disease prevention. The sentinel surveillance system of Taiwan CDC, through sentinel physicians, reports the number of outpatients suspected of infection by numerous infectious diseases from Internet. CDC can prevent the pandemic flu and occurrence of severe influenza by using this surveillance system to monitor the move of influenza-like (ILI) illness. This paper illustrates the integration of GIS with spatial statistical methods and Model Builder technology onto the analysis of temporal and spatial moves of influenza-like illness, enables one to predict both the severity and trend of disease. Spatial interpolation-the Kriging method-was used to explore the utility of the spatial trend of ILI peaks, as a method of disease surveillance. The model improves efficiency through utilization of the semi-automation techniques developed, as well as by the model's unique analysis for spatial correlation. This development introduces a new and very useful analytical tool for disease surveillance and monitoring.
Date:
2009-09
Relation:
Journal of Taiwan Association of Medical Informatics. 2009 Sep;18(3):17-31.
