Impact of Meteorological Factors on the Epidemiology of Major Enterovirus Pathogens of Hand, Foot, and Mouth Disease: A Distributed Lag Nonlinear Analysis in Fujian Province, China

Objective Investigating the impact of meteorological factors on the prevalence of the main pathogens of hand, foot, and mouth disease (HFMD) in Fujian Province, China, through spatiotemporal feature analysis and the construction of a distributed lag non-linear model (DLNM). Methods HFMD and its major pathogens EV71 and CoxA16 data from January 2017 to December 2020 in Fujian Province were obtained through the statutory infectious disease reporting surveillance system of China, and meteorological data were obtained from the national scientific meteorological data center of China. Correlation analysis was used to select meteorological variables. DLNM was constructed to investigate the impact of meteorological factors on the prevalence of EV71 and CoxA16. Results During the study period, a total of 261,434 confirmed cases of HFMD were reported in Fujian Province, with an annual incidence rate ranging from 67.62 to 243.57 per 100,000 population. The temporal distribution indicated a bimodal pattern of HFMD cases from 2017 to 2019. In 2020, HFMD cases and incidence rate significantly decreased. Spatial distribution analysis revealed that infections were predominantly concentrated in the southwestern region of Fujian, and a decreasing trend in incidence rate with increasing latitude. Correlation analysis indicated that the highest temperature (Tmax), lowest temperature (Tmin), mean temperature (MT), precipitation (PRE) and relative humidity (RHU) were positively correlated with infections, while atmospheric pressure (PRS) was negatively correlated. Analysis results from the DLNM showed that the relative risk of EV71 and CoxA16 associated with MT across various prefecture-level cities in Fujian exhibited an inverted "U" shape or a linear relationship, with a "harvesting" phenomenon observed at low MT levels. Conclusion The impact of meteorological factors on the prevalence of EV71 and CoxA16 exhibits significant spatial heterogeneity. Low MT can promote viral epidemics in the short term, and high RHU is a risk factor for viral prevalence.