This study aims to (1) investigate the associations between climatic factors and dengue; and (2) identify the susceptible subgroups. De-identified daily dengue cases in Guangzhou for 2005-2014 were obtained from the Chinese Center for Disease Control and Prevention. Weather data were downloaded from the China Meteorological Data Sharing Service System. Distributed lag non-linear models (DLNM) were used to graphically demonstrate the three-dimensional temperature-dengue association. Generalised estimating equation models (GEE) with piecewise linear spline functions were used to quantify the temperature-dengue associations. Threshold values were estimated using a broken-stick model. Middle-aged and older people, people undertaking household duties, retirees, and those unemployed were at high risk of dengue. Reversed U-shaped non-linear associations were found between ambient temperature, relative humidity, extreme wind velocity, and dengue. The optimal maximum temperature (Tmax) range for dengue transmission in Guangzhou was 21.6-32.9°C, and 11.2-23.7°C for minimum temperature (Tmin). A 1°C increase of Tmax and Tmin within these ranges was associated with 11.9% and 9.9% increase in dengue at lag0, respectively. Although lag effects of temperature were observed for up to 141 days for Tmax and 150 days for Tmin, the maximum lag effects were observed at 32 days and 39 days respectively. Average relative humidity was negatively associated with dengue when it exceeded 78.9%. Maximum wind velocity (>10.7m/s) inhibited dengue transmission. Climatic factors had significant impacts on dengue in Guangzhou. Lag effects of temperature on dengue lasted the local whole epidemic season. To reduce the likely increasing dengue burden, more efforts are needed to strengthen the capacity building of public health systems.
Keywords: Climate change; Dengue fever; Guangzhou; Infectious disease; Weather.
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