Spatio-temporal evolution patterns of influenza incidence and its nonlinear spatial correlation with environmental pollutants in China

Abstract

Abstract Background Currently, the influenza epidemic in China is at a high level and mixed with other respiratory diseases. Current studies focus on regional influenza and the impact of environmental pollutants on time series, and lack of overall studies on the national influenza epidemic and the nonlinear correlation between environmental pollutants and influenza. The unclear spatial and temporal evolution patterns of influenza as well as the unclear correlation effect between environmental pollutants and influenza epidemic have greatly hindered the prevention and treatment of influenza epidemic by relevant departments, resulting in unnecessary economic and human losses. Method This study used Chinese influenza incidence data for 2007–2017 released by the China CDC and air pollutant site monitoring data. Seasonal as well as inter monthly differences in influenza incidence across 31 provinces of China have been clarified through time series. Space-Time Cube model (STC) was used to investigate the spatio-temporal evolution of influenza incidence in 315 Chinese cities during 2007–2017. Then, based on the spatial heterogeneity of influenza incidence in China, Generalized additive model (GAM) was used to identify the correlation effect of environmental pollutants (PM2.5, PM10, CO, SO2, NO2, O3) and influenza incidence. Result The influenza incidence in China had obvious seasonal changes, with frequent outbreaks in winter and spring. The influenza incidence decreased significantly after March, with only sporadic outbreaks occurring in some areas. In the past 11 years, the influenza epidemic had gradually worsened, and the clustering of influenza had gradually expanded, which had become a serious public health problem. The correlation between environmental pollutants and influenza incidence was nonlinear. Generally, PM2.5, CO and NO2 were positively correlated at high concentrations, while PM10 and SO2 were negatively correlated. O3 was not strongly correlated with the influenza incidence. Conclusion The study found that the influenza epidemic in China was in a rapidly rising stage, and several regions had a multi-year outbreak trend and the hot spots continue to expand outward. The association between environmental pollutants and influenza incidence was nonlinear and spatially heterogeneous. Relevant departments should improve the monitoring of influenza epidemic, optimize the allocation of resources, reduce environmental pollution, and strengthen vaccination to effectively prevent the aggravation and spread of influenza epidemic in the high incidence season and areas.

Keywords

• Influenza
• Spatio-temporal evolution pattern
• Pollutants
• Generalized additive model
• Space-time cube model