Geography of two COVID-19 waves in Latvia

IF 2.6 Q1 GEOGRAPHY
Folia Geographica Pub Date : 2021-12-21 DOI:10.22364/fg.19.2
Elina Apsite-Berina, T. Skadins, G. Burgmanis, Z. Krisjane, M. Berzins
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Abstract

The COVID-19 pandemic and its waves of incidence have had a significant impact on our personal and professional lives. This has led to scholarly interest in various fields, including geography. A growing body of scholarly literature is trying to understand the reasons why some places were and still are more affected than others. The aim of this study was to shed light on the geography of the Covid-19 pandemic in Latvia and explain the geographical patterns of the pandemic during its first two waves. This was done, firstly, by mapping the number of cases per 10,000 in the municipalities of Latvia; secondly, the analysis also combined that same data with a total of eleven variables, by using bivariate correlation. The results show that during the first wave, Covid-19 incidence was relatively low. However, during the second wave, there were several large clusters of municipalities with a rather high number (over 500) confirmed Covid-19 cases per 10,000 inhabitants. Results of the correlation analysis suggest that geographical patterns of COVID-19 incidence were a result of a complex set of factors, varying throughout the country. Also, the presence of large clusters of municipalities with a rather high number of cases per capita (mostly) during the second wave points to the possible impact of proximity.
拉脱维亚两波COVID-19疫情的地理特征
2019冠状病毒病大流行及其发病率浪潮对我们的个人生活和职业生活产生了重大影响。这引起了包括地理学在内的各个领域的学术兴趣。越来越多的学术文献试图理解为什么有些地方过去和现在受到的影响比其他地方更大。本研究的目的是阐明拉脱维亚Covid-19大流行的地理位置,并解释前两波大流行期间的地理模式。首先,通过绘制拉脱维亚各市每1万人的病例数;其次,通过使用双变量相关,分析还将相同的数据与总共11个变量结合起来。结果表明,第一波疫情期间,新冠肺炎发病率相对较低。然而,在第二波疫情期间,出现了几个大型城市群,每1万名居民中确诊的Covid-19病例数量相当高(超过500例)。相关分析结果表明,COVID-19发病率的地理分布是一系列复杂因素的结果,在全国各地各不相同。此外,在第二波疫情期间,出现了人均病例数相当高(大部分)的大型城市群,这表明邻近可能产生影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Folia Geographica
Folia Geographica GEOGRAPHY-
CiteScore
4.60
自引率
30.80%
发文量
0
审稿时长
18 weeks
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