Long-term effects of meteorological factors on severe fever with thrombocytopenia syndrome incidence in eastern China from 2014 to 2020: An ecological time-series study

Background Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne disease with susceptibility influenced by meteorological factors. However, there is limited understanding of the delayed and interactive impacts of meteorological factors on SFTS incidence. Methods Daily incidence data of SFTS and corresponding meteorological factors for the Jiaodong Peninsula in northeast China were collected from January 1, 2014, to December 31, 2020. Random forest regression model, based on custom search, was performed to compare the importance of meteorological factors. Generalized additive model with quasi-Poisson regression was conducted to examine the nonlinear relationships and interactive effects using penalized spline methods. A distributed lag nonlinear model with quasi-Poisson regression was constructed to estimate exposure-lag effects of meteorological factors. Results The most important meteorological factor was weekly mean lowest temperature. The relationship between meteorological factors and SFTS incidence revealed a nonlinear and intricate pattern. Interaction analyses showed that prolonged sunshine duration posed a climatic risk within a specific temperature range for SFTS incidence. The maximum relative risk (RR) observed under extremely low temperature (-4°C) was 1.33 at lag of 15 week, while under extremely high temperature (25°C), the minimum RR was 0.65 at lag of 13 week. The RRs associated with both extremely high and low sunshine duration escalated with an increase in lag weeks. Conclusions This study underscores that meteorological factors exert nonlinear, delayed, and interactive effects on SFTS incidence. These findings highlight the importance of understanding the dependency of SFTS incidence on meteorological factors in particular climates.