Detecting the association between meteorological factors and hand, foot, and mouth disease using spatial panel data models

• Main Authors: Hao Wang, Zhaohui Du, Xianjun Wang, Yunxia Liu, Zhongshang Yuan, Yanxun Liu, Fuzhong Xue
• Format: Article
• Language: English
• Published: Elsevier 2015-05-01
• Series: International Journal of Infectious Diseases
• Subjects: Spatial panel data model; Hand, foot, and mouth disease; Meteorological factors
• Online Access: http://www.sciencedirect.com/science/article/pii/S1201971215000685

Objectives: The aim of this study was to quantify the relationship between meteorological factors and the occurrence of hand, foot, and mouth disease (HFMD) among children in Shandong Province, China, at a county level, using spatial panel data models. Methods: Descriptive analysis was applied to describe the epidemic characteristics of HFMD from January 2008 to December 2012, and then a global autocorrelation statistic (Moran's I) was used to detect the spatial autocorrelation of HFMD in each year. Finally, spatial panel data models were performed to explore the association between the incidence of HFMD and meteorological factors. Results: Moran's I at the county level were high, from 0.30 to 0.45 (p < 0.001), indicating the existence of a high spatial autocorrelation on HFMD. Spatial panel data models are more appropriate to describe the data. Results showed that the incidences of HFMD in Shandong Province, China were significantly associated with average temperature, relative humidity, vapor pressure, and wind speed. Conclusions: Spatial panel data models are useful when longitudinal data with multiple units are available and spatial autocorrelation exists. The association found between HFMD and meteorological factors makes a contribution towards advancing knowledge with respect to the causality of HFMD and has policy implications for HFMD prevention and control.