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.

Background: 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.

Methods: 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.

Findings: The cumulative effect peaked at 21.97 °C ( = 1.24, 95% CI: 1.10-1.40) and the month-specific effect peaked at 25.67 °C ( = 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 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 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.

Interpretation: 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.

Funding: National Natural Science Foundation of China (No. 82330103 and No. 42201497), Youth Innovation Promotion Association (No. 2023000117), and the Wellcome Trust [220211].