[Analysis on impact of meteorological factors on incidence of hand, foot and mouth disease based on Bayes spatial-temporal theory].

OBJECTIVE

To understand the impact of meteorological factors on the incidence of hand, foot and mouth disease (HFMD) and the epidemiological characteristics of HFMD in China.

METHODS

Bayesian hierarchical model [Besag, York, and Mollie' (BYM) model] was used to fit the data. The fitting effects of uncorrelated heterogeneity (UH) model, correlated heterogeneity (CH) model and spatial and temporal interaction model were compared and the best model was selected to analyze the meteorological factors influencing the incidence of HFMD.

RESULTS

The UH+CH model with spatial and temporal interaction had best fitting effect (DIC=35,507.2). Rainfall (RR=1.0517, 95% CI: 1.0504-1.0525), average temperature (RR=1.0896, 95% CI: 1.078 1-1.1069), average relative humidity (RR=1.0890, 95% CI: 1.0821-1.0912), average air pressure (RR=1.0764, 95% CI: 1.0748-1.0779) and hours of sunshine (RR=1.0851, 95% CI: 1.0798-1.0875) were the meteorological factors influencing the incidence of HFMD.

CONCLUSION

The incidence of HFMD had spatial and temporal clustering characteristics. The meteorological factors were closely related with the incidence of HFMD.