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First wave of SARS-COV2 in Europe: Study and typology of the 15 worst affected European countries
Population, Space and Place ( IF 2.6 ) Pub Date : 2021-10-26 , DOI: 10.1002/psp.2534
Alexandra Tragaki 1 , Jean-Luc Richard 2
Affiliation  

Since 11 March 2020 when officially declared a global pandemic, Covid-19 (or SARS-COV2) has turned out to be a multifaceted disease differently affecting countries and individuals. What makes certain countries more vulnerable than others has attracted the interest of scientists from various disciplines. This paper intends to compare the impact of demographic parameters, population health conditions and policy actions on prevalence and fatality levels of Covid-19 during the first 3 months since its declaration of global pandemic. A country-level exploratory analysis has been conducted in order to assess how demography, national health conditions and measures taken interact and condition the disease outcomes. Analysis relies on publicly available data on Covid-19 reported cases, deaths and number of persons tested. Those data are combined with demographic parameters (sex ratio, mean age, population density and life expectancy), health data (cardiovascular death rate, diabetes prevalence, share of smokers among males and females and number of hospital beds) and information about relative national policies aiming the management of the pandemic (lockdown timing and duration). Our analysis confirms the diversity of factors and the complexity of their interaction in explaining the propagation and fatality of the disease across Europe. Our findings question some well-established attitudes concerning the role of demographic variables and public health conditions in the spread of the disease.

中文翻译:

欧洲第一波 SARS-COV2:15 个受影响最严重的欧洲国家的研究和类型学

自 2020 年 3 月 11 日正式宣布全球大流行以来,Covid-19(或 SARS-COV2)已被证明是一种多方面的疾病,对国家和个人产生不同的影响。是什么让某些国家比其他国家更脆弱,吸引了不同学科科学家的兴趣。本文旨在比较 Covid-19 自宣布全球大流行以来的前 3 个月内人口统计参数、人口健康状况和政策行动对 Covid-19 流行率和死亡率水平的影响。已经进行了国家层面的探索性分析,以评估人口统计、国家卫生状况和采取的措施如何相互作用并影响疾病结果。分析依赖于关于 Covid-19 报告病例、死亡和检测人数的公开数据。这些数据与人口统计参数(性别比、平均年龄、人口密度和预期寿命)、健康数据(心血管死亡率、糖尿病患病率、男性和女性吸烟者比例以及医院床位数量)和有关国家政策的信息相结合旨在管理大流行(锁定时间和持续时间)。我们的分析证实了因素的多样性及其相互作用的复杂性,从而解释了这种疾病在欧洲的传播和致死率。我们的研究结果质疑一些关于人口变量和公共卫生条件在疾病传播中的作用的既定态度。男性和女性吸烟者的比例以及医院病床的数量)以及有关旨在管理大流行的相关国家政策的信息(锁定时间和持续时间)。我们的分析证实了因素的多样性及其相互作用的复杂性,从而解释了这种疾病在欧洲的传播和致死率。我们的研究结果质疑一些关于人口变量和公共卫生条件在疾病传播中的作用的既定态度。男性和女性吸烟者的比例以及医院病床的数量)以及有关旨在管理大流行的相关国家政策的信息(锁定时间和持续时间)。我们的分析证实了因素的多样性及其相互作用的复杂性,从而解释了这种疾病在欧洲的传播和致死率。我们的研究结果质疑一些关于人口变量和公共卫生条件在疾病传播中的作用的既定态度。
更新日期:2021-10-26
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