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Based on the spatial units of community, village and town in Beijing, the relationship betweent HFMD morbidity and the potential risk factors has been examined. According to the 6 selected risk factors (namely population density, disposable income of urban residents, the number of medical and health institutions, the number of hospital beds, average annual temperature and average annual relative humidity) significantly related to HFMD morbidity, the prediction performance of Classical Linear Regression Model(CLRM) and Spatial Lag Model(SLM) has been compared. The results showed that SLM achieved better effect and R square reached 0.82. It was showed that spatial effect played the crucial role in the HFMD morbidity prediction and its contribution attained 88%. However, CLRM showed low prediction accuracy and bias estimation. It was demonstrated that including spatial effect item into CLRM could greatly improve the performance of HFMD morbidity prediciton model.

Using Spatial Prediction Model to Analyze Driving Forces of the Beijing 2008 HFMD Epidemic