Quantifying the risk of hand, foot, and mouth disease (HFMD) attributable to meteorological factors in East China: A time series modelling study

Hand, foot, and mouth disease (HFMD) is a widespread infectious disease in China. Associated meteorological factors have been widely studied, but their attributable risks have not been well quantified. The study aimed to quantify the HFMD burden attributable to temperature and other meteorological factors. The daily counts of HFMD and meteorological factors in all 574 counties of East China were obtained for the period from 2009 to 2015. The exposure-lag-response relationships between meteorological factors and HFMD were quantified by using a distributed lag non-linear model for each county and the estimates from all the counties were then pooled using a multivariate mete-regression model. Attributable risks were estimated for meteorological variables according to the exposure-lag-response relationships obtained before. The study included 4,058,702 HFMD cases. Non-optimal values of meteorological factors were attributable to approximately one third of all HFMD cases, and the attributable numbers of non-optimal ambient temperature, relative humidity, wind speed and sunshine hours were 815,942 (95% CI: 796,361-835,888), 291,759 (95% CI: 226,183-358,494), 92,060 (95% CI: 59,655-124,738) and 62,948 (95% CI: 20,621-105,773), respectively. The exposure-response relationship between temperature and HFMD was non-linear with an approximate "M" shape. High temperature had a greater influence on HFMD than low temperature did. There was a geographical heterogeneity related to water body, and more cases occurred in days with moderate high and low temperatures than in days with extreme temperature. The effects of meteorological factors on HFMD were generally consistent across subgroups. Non-optimal temperature is the leading risk factor of HFMD in East China, and moderate hot and moderate cold days had the highest risk. Developing subgroup-targeted and region-specific programs may minimize the adverse consequences of non-optimum weather on HFMD risk.