The effect of meteorological factors on severe fever with thrombocytopenia syndrome: Evidence from 34 Chinese cities.

BACKGROUND

Severe fever with thrombocytopenia syndrome (SFTS) is a climate-sensitive infectious disease, and its spatial distribution has been expanding in recent years. This study aimed to investigate the influence of meteorological factors on SFTS incidence.

METHODS

Data on SFTS was extracted from the Infectious Disease Surveillance Report Management System from January 1, 2011 to December 31, 2023. A two-stage hierarchical analytical framework was employed in this study. First, a distributed lag nonlinear model was utilized to characterize the nonlinear exposure-response relationships between meteorological factors and the incidence of SFTS at the municipal level. Second, a multivariate meta-analysis was conducted to synthesize city-specific effect estimates, with explicit adjustment for inter-regional heterogeneity.

RESULTS

From 2011 to 2023, 34 cities with cumulative cases ≥100 were included in the final analysis, which accounted for 94.59 % of the total SFTS cases during the same period in mainland China. The incidence risk of SFTS was positively correlated with temperature, relative humidity, precipitation, normalized difference vegetation index, and land cover, but negatively correlated with atmospheric pressure. The exposure-response relationship between average temperature and SFTS risk exhibited a single peak at 24.70 °C (RR = 2.78, 95 % CI: 1.14-6.79). Stratified analysis revealed the highest temperature-related risk in Eastern China at 27.50 °C (RR = 9.85, 95 % CI: 1.87-51.76), which was significantly elevated compared to central and northeastern regions. Regional variability was also observed for precipitation: the overall minimum risk occurred at 15.30 mm (RR = 0.49, 95 % CI: 0.24-0.98), whereas the risk nadir in Eastern China was at 16.02 mm monthly precipitation (RR = 0.29, 95 % CI: 0.10-0.80).

CONCLUSIONS

This study demonstrates that temperature and precipitation significantly influence SFTS incidence, with effects lagging consistently by 1-2 months. These findings can be integrated into China's Smart Multi-Point Surveillance System by incorporating region-specific meteorological thresholds to trigger early warnings. The system could then activate targeted interventions, such as tick control measures, accounting for the observed 1-2 month lag between climatic conditions and disease occurrence. Such climate-adaptive approaches would enhance the precision and timeliness of SFTS prevention and control efforts nationwide.