使用机器学习算法分析罗马尼亚的流动性、COVID-19病例和病毒繁殖率数据

G. Ene, A. Bâra, S. Oprea, Costin Baroiu, Dragos-Catalin Barbu
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引用次数: 1

摘要

本文研究了罗马尼亚COVID-19大流行期间封锁措施对人口流动的影响。包括罗马尼亚在内的许多国家对受感染的人采取了检疫和隔离措施,试图阻止病毒的传播和病例数量的迅速增加,这给医院带来了巨大压力。这些措施减缓了经济,导致失业,增加了恐慌或焦虑,对人们的心理产生了巨大影响。流动性数据被用作社会距离的度量表示,因此,将流动性数据集与covid -19相关数据相结合可能支持分析病毒效应与流动性之间的关系,并相应地支持分析人口流动性对病毒传播的影响。不可否认的是,实施的限制影响了商业环境,我们的目的是调查COVID-19病例数、病毒繁殖率以及向零售店和工作场所流动的变化之间的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mobility, COVID-19 cases and virus reproduction rate data analysis for Romania using Machine Learning Algorithms
This paper examines the effect of lockdown measures on population mobility during the COVID-19 pandemic in Romania. Many countries, including Romania, have adopted quarantine and isolation for infected people in attempting to stop the virus transmission and the rapid escalation of the number of cases, which has put great pressure on hospitals. These measures have slowed down the economy leading to the loss of jobs with a massive impact on people's psychology by increasing panic or anxiety. Mobility data is used as a measurement representation of social distancing and therefore, combining mobility data sets with COVID-19-related data might support the analysis between the virus effects and mobility and, correspondingly, the population mobility impact on virus transmission. It is undeniable that the imposed restrictions have influenced the business environment, our aim being to investigate the relationship between the number of COVID-19 cases, the virus reproduction rate, and the changes in mobility toward retail outlets and workplaces.
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