Li Qiongfen

We are developing a Bayesian surveillance system for realtime surveillance and characterization of outbreaks that incorporates a variety of data elements, including free-text clinical reports. An existing natural language processing (NLP) system called Topaz is being used to extract clinical data from the reports. Moving the NLP system from a research project to a real-time service has presented many challenges.

Objective

Adapt an existing NLP system to be a useful component in a system performing real-time surveillance.

Influenza is a highly contagious, acute respiratory disease that causes periodic seasonal epidemics and global pandemics[1]. Yunnan Province is characterized by poverty, multi-ethnic, and cross-border movement, which maybe be susceptible of influenza (Fig-1). Finding from spatial patter of ILI will promote to control and prevent the respiratory diseases epidemic

Objective

The purpose of the study was to determine spatial clustering of the spread of influenza like illness (ILI) epidemic in Yunnan province, China with the aim of producing useful information for prevention and control measures.