Ambient temperature and relative humidity as possible drivers of the hand, foot, and mouth disease epidemics in Zhejiang Province, China

Hand, foot, and mouth disease (HFMD) is a common communicable disease among children and has been a global health problem in recent decades. Literature has shown that meteorological factors possibly drive the epidemic of HFMD, but the natures differ across regions. To elucidate the associations between meteorological factors and the epidemic of HFMD in Zhejiang province, China, the incidence rate and the number of probable and laboratory-confirmed cases of HFMD as well as meteorological factors (ambient temperature, relative humidity, total rainfall, wind speed, and total sunshine duration) during the year of 2013–2017 in the province were modelled by the Bayesian hierarchical Poisson spatiotemporal model with distributed lag nonlinear components, so as to capture spatiotemporal associations and potentially nonlinear or lagged effects of the meteorological factors. During the study period, there were altogether 689,898 HFMD cases in Zhejiang province, and the disease exhibited a strong spatiotemporal association. On average, Ningbo had the highest weekly incidence rate of 6.83/100,000. The cumulative adjusted relative risk (ARR) increased with average ambient temperature until 24.6 °C (ARR = 1.14, 95% CI: 1.04–1.30), at which the pattern reverted. The cumulative ARR also increased statistically significantly with average relative humidity. It was estimated that 1% increase in relative humidity corresponded to 1.07%–1.16% increase in ARR. Total rainfall, average wind speed, and total sunshine duration were not statistically significantly associated with the incidence rate. In conclusion, the existence of the associations between meteorological factors and the incidence rate of HFMD implies that the local government could make use of meteorological information for disease surveillance, allowing early preparation for the outbreak of HFMD when favorable conditions (wet and moderately hot) are forecasted, in order to reduce the heavy burden induced by the disease.