Data on: Projecting spatiotemporal dynamics of severe fever with thrombocytopenia syndrome in the mainland of China

This dataset is the data used in the paper of Global change biology entitled \"Projecting spatiotemporal dynamics of severe fever with thrombocytopenia syndrome in the mainland of China\". We use an integrated multi-model, multi-scenario framework to assess the impact of global climate change on SFTS disease in the mainland of China. The SFTS incidence in three time periods (2030-2039, 2050-2059, 2080-2089) is predicted to be increased as compared to the 2010s in the context of various RCPs. The projected spatiotemporal dynamics of SFTS will be heterogeneous across provinces. Notably, we predict possible outbreaks in Xinjiang and Yunnan in the future, where only sporadic cases have been reported previously. These findings highlight the need for population awareness of SFTS in endemic regions, and enhanced monitoring in potential risk areas.Â

本数据集为发表于《Global Change Biology》（《全球变化生物学》）期刊、题为"Projecting spatiotemporal dynamics of severe fever with thrombocytopenia syndrome in the mainland of China"的学术论文所使用的研究数据。本研究采用集成多模型、多情景框架，评估全球气候变化对中国内地发热伴血小板减少综合征（Severe Fever with Thrombocytopenia Syndrome, SFTS）疫情的影响。在不同典型浓度路径（Representative Concentration Pathways, RCPs）情景下，相较于2010年代，2030-2039年、2050-2059年及2080-2089年三个时段的SFTS发病率均呈上升趋势。SFTS的预测时空动态在各省域间存在显著异质性。值得关注的是，本研究预测新疆与云南两地未来或出现SFTS暴发疫情，而此前该两地仅报告过零星散发病例。本研究结果凸显了在SFTS流行区域提升公众疾病认知、在潜在风险区域强化监测工作的必要性。