Sarah Habershon, Kolja Nenoff, Guido Kraemer, Lennart Schüler, Heinrich Zozmann, Justin M Calabrese, Sabine Attinger, Miguel D Mahecha
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The spatiotemporal dynamics of COVID-19 in Europe: time-series clustering maps 5 distinct trajectories to spatial patterns.
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.
期刊介绍:
Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.