RESEARCH ARTICLE Time Series Analyses of Hand, Foot and Mouth Disease Integrating Weather Variables

Background The past decade witnessed an increment in the incidence of hand foot mouth disease (HFMD) in the Pacific Asian region; specifically, in Guangzhou China. This emphasized the requirement of an early warning system designed to allow the medical community to better prepare for outbreaks and thus minimize the number of fatalities. Methods Samples from 1,556 inpatients (hospitalized) and 11,004 outpatients (non-admitted) diag-nosed with HFMD were collected in this study from January 2009 to October 2013. Season-al Autoregressive Integrated Moving Average (SARIMA) model was applied to establish high predictive model for inpatients and outpatient as well as three viral serotypes (EV71, Pan-EV and CA16). To integrate climate variables in the data analyses, data from eight cli-mate variables were simultaneously obtained during this period. Significant climate variable identified by correlation analyses was executed to improve time series modeling as external repressors