{"title":"时间上的波动,但空间上的波动——德国新冠肺炎疫情严重程度分析","authors":"Andreas Kuebart , Martin Stabler","doi":"10.1016/j.sste.2023.100605","DOIUrl":null,"url":null,"abstract":"<div><p>While pandemic waves are often studied on the national scale, they typically are not distributed evenly within countries. This study presents a novel approach to analyzing the spatial-temporal dynamics of the COVID-19 pandemic in Germany. By using a composite indicator of pandemic severity and subdividing the pandemic into fifteen phases, we were able to identify similar trajectories of pandemic severity among all German counties through hierarchical clustering. Our results show that the hotspots and cold spots of the first four waves were relatively stationary in space. This highlights the importance of examining pandemic waves on a regional scale to gain a more comprehensive understanding of their dynamics. By combining spatial autocorrelation and spatial-temporal clustering of time series, we were able to identify important patterns of regional anomalies, which can help target more effective public health interventions on a regional scale.</p></div>","PeriodicalId":46645,"journal":{"name":"Spatial and Spatio-Temporal Epidemiology","volume":"47 ","pages":"Article 100605"},"PeriodicalIF":2.1000,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Waves in time, but not in space – an analysis of pandemic severity of COVID-19 in Germany\",\"authors\":\"Andreas Kuebart , Martin Stabler\",\"doi\":\"10.1016/j.sste.2023.100605\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>While pandemic waves are often studied on the national scale, they typically are not distributed evenly within countries. This study presents a novel approach to analyzing the spatial-temporal dynamics of the COVID-19 pandemic in Germany. By using a composite indicator of pandemic severity and subdividing the pandemic into fifteen phases, we were able to identify similar trajectories of pandemic severity among all German counties through hierarchical clustering. Our results show that the hotspots and cold spots of the first four waves were relatively stationary in space. This highlights the importance of examining pandemic waves on a regional scale to gain a more comprehensive understanding of their dynamics. By combining spatial autocorrelation and spatial-temporal clustering of time series, we were able to identify important patterns of regional anomalies, which can help target more effective public health interventions on a regional scale.</p></div>\",\"PeriodicalId\":46645,\"journal\":{\"name\":\"Spatial and Spatio-Temporal Epidemiology\",\"volume\":\"47 \",\"pages\":\"Article 100605\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2023-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Spatial and Spatio-Temporal Epidemiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1877584523000424\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spatial and Spatio-Temporal Epidemiology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1877584523000424","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Waves in time, but not in space – an analysis of pandemic severity of COVID-19 in Germany
While pandemic waves are often studied on the national scale, they typically are not distributed evenly within countries. This study presents a novel approach to analyzing the spatial-temporal dynamics of the COVID-19 pandemic in Germany. By using a composite indicator of pandemic severity and subdividing the pandemic into fifteen phases, we were able to identify similar trajectories of pandemic severity among all German counties through hierarchical clustering. Our results show that the hotspots and cold spots of the first four waves were relatively stationary in space. This highlights the importance of examining pandemic waves on a regional scale to gain a more comprehensive understanding of their dynamics. By combining spatial autocorrelation and spatial-temporal clustering of time series, we were able to identify important patterns of regional anomalies, which can help target more effective public health interventions on a regional scale.