Combined effects of hydrological conditions and socioeconomic factors on the seasonal dynamics of severe fever with thrombocytopenia syndrome in China, 2011-2022: a modelling study.

Abstract

Severe fever with thrombocytopenia syndrome (SFTS) is a tick-borne viral hemorrhagic fever with expanding geographical range. The determinants of the seasonal dynamics of SFTS remain poorly understood. Monthly SFTS cases from 604 counties in five provinces with high-notification rate in China (2011-2022) were analyzed using hierarchical Bayesian spatiotemporal and distributed lag nonlinear models. Cumulative and month-specific effects of meteorological factors were assessed, with socioeconomic factors as modifiers. The cumulative effect peaked at 21.97 °C (<i>RR</i> = 1.24, 95% CI: 1.10-1.40) and the month-specific effect peaked at 25.67 °C (<i>RR</i> = 1.38, 95% CI: 1.26-1.51) without time lag. Increased precipitation significantly amplified the risk of SFTS with a notable lag effect observed. Both drought and wet conditions heightened the risk of SFTS occurrence substantially, with cumulative <i>RR</i> peaking at 3.13 (95% CI: 1.58-6.23) for Standardized Precipitation Evapotranspiration Index (SPEI-1) of -2.5, indicating drought conditions, and peaking at 1.51 (95% CI: 1.00-2.27) for SPEI-1 of 2.16, indicating wet conditions. The highest month-specific <i>RR</i> was observed at an SPEI-1 of -2.5 with a 2-month lag and at 1.81 with a 1-month lag, respectively. The risk of SFTS was higher in low-urbanization areas during drought, while was higher in high-urbanization areas with wet conditions. Climatic factors significantly influence SFTS dynamics, with socioeconomic conditions modifying these effects. Integrating climate factors into surveillance and early warning systems is essential for targeted prevention and control. National Natural Science Foundation of China (No. 82330103 and No. 42201497), Youth Innovation Promotion Association (No. 2023000117), and the Wellcome Trust [220211].