Habershon Sarah, Nenoff Kolja, Kraemer Guido, Schüler Lennart, Zozmann Heinrich, Calabrese Justin M, Attinger Sabine, Mahecha Miguel D
Institute for Earth System Sciences and Remote Sensing, Talstraße 35, 04103, Leipzig, Germany.
Helmholtz Centre for Environmental Research, Leipzig, Germany.
Popul Health Metr. 2025 Aug 5;23(1):44. doi: 10.1186/s12963-025-00405-w.
The COVID-19 pandemic affected Europe unevenly, with surges in infections and deaths fluctuating across different regions and time periods. Hyper-localised hotspots and staggered timelines created intense, asynchronous waves of infections and deaths that distort country-level and cumulative data, obscuring the pandemic's spatiotemporal dynamics through aggregation. Despite extensive research comparing states and analysing subnational variance within individual countries, the detailed subnational and transnational dynamics of the COVID-19 pandemic across Europe as a whole have not been comprehensively described. Here we show that time-series clustering, applied to weekly excess mortality estimates for subnational NUTS3 administrative regions of 27 countries in Europe, identifies five distinct pandemic trajectories which map to spatial patterns. The trajectories comprise two subgroups, representing contrasting pandemic dynamics in eastern and western Europe. Western Europe exhibits concentric arrangements of mortality impact, with secondary and tertiary impact zones surrounding outbreak epicenters. Eastern Europe exhibits internally homogeneous spatial dynamics, possibly due to the deferral of the first major mortality wave.
新冠疫情对欧洲的影响并不均衡,不同地区和时间段的感染和死亡人数激增情况有所波动。高度局部化的热点地区和交错的时间线造成了强烈的、不同步的感染和死亡浪潮,这些浪潮扭曲了国家层面和累计数据,通过汇总掩盖了疫情的时空动态。尽管有大量研究比较了不同国家并分析了单个国家内部的次国家差异,但整个欧洲新冠疫情详细的次国家和跨国动态尚未得到全面描述。在此我们表明,将时间序列聚类应用于欧洲27个国家次国家NUTS3行政区的每周超额死亡率估计,可以识别出五个不同的疫情轨迹,这些轨迹对应着空间模式。这些轨迹包括两个亚组,代表了东欧和西欧截然不同的疫情动态。西欧呈现出死亡率影响的同心圆式分布,疫情爆发中心周围有二级和三级影响区。东欧呈现出内部均匀的空间动态,这可能是由于第一波主要死亡浪潮的延迟所致。