Publication Details |
| Category | Text Publication |
| Reference Category | Journals |
| DOI | 10.1186/s12963-025-00405-w |
Licence  |
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| Title (Primary) | The spatiotemporal dynamics of COVID-19 in Europe: time-series clustering maps 5 distinct trajectories to spatial patterns |
| Author | Habershon, S.; Nenoff, K.; Kraemer, G.; Schüler, L.
; Zozmann, H.; Calabrese, J.M.; Attinger, S.; Mahecha, M.D. |
| Source Titel | Population Health Metrics |
| Year | 2025 |
| Department | OEKON; CHS; MET |
| Volume | 23 |
| Page From | art. 44 |
| Language | englisch |
| Topic | T5 Future Landscapes |
| Abstract | 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. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=31190 |
| Habershon, S., Nenoff, K., Kraemer, G., Schüler, L., Zozmann, H., Calabrese, J.M., Attinger, S., Mahecha, M.D. (2025): The spatiotemporal dynamics of COVID-19 in Europe: time-series clustering maps 5 distinct trajectories to spatial patterns Popul. Health Metr. 23 , art. 44 10.1186/s12963-025-00405-w |
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