Explaining COVID-19 mortality rates in the first wave in Europe

Q4 Mathematics

Model Assisted Statistics and Applications Pub Date : 2021-08-27 DOI:10.3233/mas-210534

G. Cordeiro, Dalson Figueiredo, Lucas Silva, E. M. Ortega, F. Prataviera

引用次数: 5

Abstract

The beta regression has been received considerable attention in the last decade because of its applications to proportional data in several fields. We study the variability of coronavirus death rates in the first wave of twenty European countries using the beta regression with two systematic components for the mean and dispersion parameters. We prove empirically that the population density, proportion of urban population, hospital beds per 100 thousand and running time explain the variability of the COVID-19 death rates in the first wave of these countries.

查看原文本刊更多论文

解释欧洲第一波新冠肺炎死亡率

在过去的十年里，贝塔回归由于其在几个领域的比例数据应用而受到了相当大的关注。我们使用β回归法研究了第一波20个欧洲国家冠状病毒死亡率的变异性，该回归法具有两个系统成分的平均值和离散度参数。我们实证证明，人口密度、城市人口比例、每10万张病床和运行时间解释了这些国家第一波新冠肺炎死亡率的可变性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Model Assisted Statistics and Applications Mathematics-Applied Mathematics

CiteScore

1.00

自引率

0.00%

发文量

期刊介绍： Model Assisted Statistics and Applications is a peer reviewed international journal. Model Assisted Statistics means an improvement of inference and analysis by use of correlated information, or an underlying theoretical or design model. This might be the design, adjustment, estimation, or analytical phase of statistical project. This information may be survey generated or coming from an independent source. Original papers in the field of sampling theory, econometrics, time-series, design of experiments, and multivariate analysis will be preferred. Papers of both applied and theoretical topics are acceptable.