Mapping the occasionality of inevitable dengue fever prevalence in China

Abstract

Abstract Background Dengue fever (DF) is an acute mosquito-borne viral infectious disease in the world, and increasing DF outbreaks in China have posed serious impacts on public health in recent years. Thus, comprehensively investigating spatiotemporal features and driving or restrictive factors of DF epidemics is critical for the improvement of intervention capacity against this disease. Methods Two famous dividing lines (Hu Line and Q-H Line) were applied to divide the mainland into four regions for geographically characterizing China’s DF prevalence. We defined the stages with suitable relative humidity, temperature, and precipitation as basic time windows for the mosquito vectors’ activities. The Random Forest (RF) model was employed to fit the relationships between local epidemics and included climatic and socioeconomic factors, quantify these factors’ contribution, and then map the city-level risk of local DF prevalence. Results The situation of China’s DF epidemics was increasingly serious due to ascending intensities of local prevalence triggered by more frequently imported cases. The cities with DF cases, together with their frequencies and intensities presented clear geographical disparities on the city scale, and well matched with the time windows for either DF transmission (95.74%) or mosquito vectors’ activities (83.59%). Among these included factors, the imported cases acted as the driving factor of local epidemics in the region I and III because of not only their strongest association (r=0.43, P<0.01; r=0.46, P<0.01) but also the largest contribution (24.82% and 31.01%). Moreover, in terms of SHAP values, the imported DF cases possessed a steady promoting impact on local epidemics, while the rest 11 inputs had comprehensive promoting or inhibiting effects with different inflexion values. Besides, the RF models considering the time windows owned higher testing AUC value (0.92) while fitting the relationships between local DF epidemics and potential factors, by which we successfully identified about 96% of the cities with the highest and higher risks of local DF prevalence. Conclusions China is being confronted with increasingly larger intensities of occasionally localized DF epidemics triggered by unavoidable higher frequencies of imported epidemics. This study would supply useful clues for the health authorities improving their intervention capacity against this disease.