Bayesian spatiotemporal analysis for association of environmental factors with hand, foot, and mouth disease in Guangdong, China

Hand, foot, and mouth disease (HFMD) remains a significant public health and economic burden in parts of China, particularly Guangdong Province. Although the association between meteorological factors and HFMD has been well documented, significant gaps remain in our understanding of the potential impact of environmental factors. Using county-level monthly HFMD data from China CDC and environmental data from multiple sources, we used spatiotemporal Bayesian models to evaluate the association between HFMD and environmental factors including vegetation index, proportion of artificial surface, road capacity, temperature and humidity, and assessed the spatial and temporal dynamic of the association. Statistically significant correlation coefficients from −0.056 to 0.36 (all P < 0.05) were found between HFMD incidence and all environmental factors. The contributions of these factors for HFMD incidence were estimated to be 16.32%, 12.31%, 14.61%, 13.53%, and 2.63%. All environmental factors including vegetation index (Relative Risk: 0.889; Credible Interval: 0.883–0.895), artificial surface (1.028; 1.022–1.034), road capacity (1.033; 1.028–1.038), temperature (1.039; 1.028–1.05), and relative humidity (1.015; 1.01–1.021) were statistically retained in the final spatiotemporal model. More comprehensive environmental factors were identified as associating with HFMD incidence. Taking these environmental factors into consideration for prevention and control strategy might be of great practical significance.