Spatial-temporal mapping of hand foot and mouth disease and the long-term effects associated with climate and socio-economic variables in Sichuan Province, China from 2009 to 2013.

BACKGROUND

Hand, foot and mouth disease (HFMD) is a common infectious disease caused by enteroviruses. The annual HFMD incidence increased from 37.6/100,000 in 2008 to 139.6/100,000 in 2014 in mainland China. In this study, we try to model spatial-temporal association between HFMD incidence and climate and socio-economic variables.

METHODS

The annual numbers of reported cases of HFMD and populations from 2009 to 2013 were obtained from the Chinese infectious disease surveillance system. The climate data were obtained from a data sharing website hosted by the China Meteorological Administration. The socio-economic data were obtained from the statistic Yearbook of Sichuan province. Moran's I statistics were used to detect the counties' global spatial clusters. The hierarchical Bayesian spatial temporal interactive models were used to analyze the association between the annual HFMD incidence rate and climate variables.

RESULTS

An increasing trend in the annual HFMD incidence was detected in south-western counties. Spatial temporal clusters existed in Sichuan Province. A highly county level spatial structured RR (relative risk, RR) of HFMD incidence was detected in the northern and central of Sichuan Province. Annual HFMD incidence of counties were positively associated with the average annual temperature (RR:1.171, 95%CI:1.0435-1.3134), the second quartile of the per capital of GDP (reference: the first quartile of GDP, RR: 1.258, 95%CI: 1.0418-1.5200), the third quartile of per capital of GDP (RR:1.7726, 95%CI:1.3709-2.2907) and the fourth quartile of the per capital GDP (RR:1.9026, 95%CI1.3318-2.7086).

CONCLUSION

The HFMD incidence exhibited a heterogeneous spatial-temporal distribution in Sichuan Province. In the counties with greater wealth, the temperature was the primary risk factor, whereas in the counties with less wealth, GDP was the primary risk factor attributed to the spatial structured of HFMD incidence. Different preventive measures should be implemented in counties with different economic conditions.