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欧洲在疫情爆发的前 12 个高峰周内的 COVID-19 病例和死亡分布。

Distribution of COVID-19 cases and deaths in Europe during the first 12 peak weeks of outbreak.

机构信息

Department of Statistics and Operations Research, Faculty of Economics and Management, Slovak University of Agriculture in Nitra, Nitra, Slovak Republic.

Environment a.s., Centre for Biostatistics and Environment, Nitra, Slovak Republic.

出版信息

Cent Eur J Public Health. 2021 Mar;29(1):9-13. doi: 10.21101/cejph.a6394.

Abstract

OBJECTIVE

The aim of the study was to identify similar WHO European countries in COVID-19 incidence and mortality rate during the first 12 peak weeks of pandemic outbreak to find out whether exact coherent parts of Europe were more affected than others, and to set relationship between age and higher COVID-19 mortality rate.

METHODS

COVID-19 cases and deaths from 28 February to 21 May 2020 of 37 WHO European countries were aggregated into 12 consecutive weeks. The fuzzy C-means clustering was performed to identify similar countries in COVID-19 incidence and mortality rate. Pearson product-moment correlation coefficient and log-log linear regression analyses were performed to set up relation between COVID-19 mortality rate and age. Mann-Whitney (Wilcoxon) test was used to explore differences between countries possessing higher mortality rate and age.

RESULTS

Based on the highest value of the coefficient of overall separation five clusters of similar countries were identified for incidence rate, mortality rate and in total. Analysis according to weeks offered trends where progress of COVID-19 incidence and mortality rate was visible. Pearson coefficient (0.69) suggested moderately strong connection between mortality rate and age, Mann-Whitney (Wilcoxon) test proved statistically significant differences between countries experiencing higher mortality rate and age vs. countries having both indicators lower (p < 0.001). Log-log linear regression analysis defined every increase in life expectancy at birth in total by 1% meant growth in mortality rate by 22% (p < 0.001).

CONCLUSION

Spain, Belgium and Ireland, closely followed by Sweden and Great Britain were identified as the worst countries in terms of incidence and mortality rate in the monitored period. Luxembourg, Belarus and Moldova accompanied the group of the worst countries in terms of incidence rate and Italy, France and the Netherland in terms of mortality rate. Correlation analysis and the Mann-Whitney (Wilcoxon) test proved statistically significant positive relationship between mortality rate and age. Log-log linear regression analysis proved that higher age accelerated the growth of mortality rate.

摘要

目的

本研究旨在确定 COVID-19 发病和死亡率在大流行爆发的前 12 个高峰周期间相似的世界卫生组织欧洲国家,以了解是否欧洲的某些特定地区比其他地区受到的影响更大,并确定年龄与 COVID-19 高死亡率之间的关系。

方法

将 2020 年 2 月 28 日至 5 月 21 日期间 37 个世界卫生组织欧洲国家的 COVID-19 病例和死亡人数汇总到 12 个连续周内。使用模糊 C-均值聚类方法确定 COVID-19 发病率和死亡率相似的国家。进行 Pearson 积矩相关系数和对数-对数线性回归分析,以建立 COVID-19 死亡率与年龄之间的关系。使用 Mann-Whitney(Wilcoxon)检验探索死亡率较高和年龄较大的国家之间的差异。

结果

基于总体分离系数的最高值,为发病率、死亡率和总体确定了五个相似国家的聚类。按周分析提供了 COVID-19 发病率和死亡率的进展情况。Pearson 系数(0.69)表明死亡率与年龄之间存在中度强相关性,Mann-Whitney(Wilcoxon)检验证明死亡率较高和年龄较大的国家与死亡率和年龄均较低的国家之间存在统计学显著差异(p<0.001)。对数-对数线性回归分析确定了出生时预期寿命每增加 1%,死亡率就增加 22%(p<0.001)。

结论

西班牙、比利时和爱尔兰被确定为监测期间发病率和死亡率最高的国家,紧随其后的是瑞典和英国。卢森堡、白俄罗斯和摩尔多瓦与发病率最高的国家一起,意大利、法国和荷兰与死亡率最高的国家一起。相关性分析和 Mann-Whitney(Wilcoxon)检验证明了死亡率与年龄之间存在统计学显著的正相关关系。对数-对数线性回归分析证明,年龄较大加速了死亡率的增长。

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