COVID-19期间研究的可重复性:基于空间分析视角的人口密度与基本繁殖率案例检验

IF 3.3 3区 地球科学 Q1 GEOGRAPHY
Antonio Paez
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引用次数: 14

摘要

2019年,新型冠状病毒(SARS-CoV-2)和全球新冠肺炎大流行的出现,推动了科学研究的爆炸式增长。唉,文献中的许多研究都缺乏可重复的条件,最近关于人口密度与SARS-CoV-2基本繁殖数之间关系的出版物也不例外。相对较少的论文充分共享代码和数据,这不仅阻碍了验证,而且阻碍了额外的实验。本文以可重复研究为例,展示了空间分析在COVID-19流行病学研究中的潜力。透明和开放意味着独立的研究人员只需付出适度的努力,就可以验证研究结果,并酌情使用不同的方法。鉴于形势的高度利害关系,重要的是科学发现——良好的政策所依赖的科学发现——必须尽可能有力;正如经验例子所示,再现性是确保这一点的关键之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Reproducibility of Research During COVID-19: Examining the Case of Population Density and the Basic Reproductive Rate from the Perspective of Spatial Analysis

Reproducibility of Research During COVID-19: Examining the Case of Population Density and the Basic Reproductive Rate from the Perspective of Spatial Analysis

The emergence of the novel SARS-CoV-2 coronavirus and the global COVID-19 pandemic in 2019 led to explosive growth in scientific research. Alas, much of the research in the literature lacks conditions to be reproducible, and recent publications on the association between population density and the basic reproductive number of SARS-CoV-2 are no exception. Relatively few papers share code and data sufficiently, which hinders not only verification but additional experimentation. In this article, an example of reproducible research shows the potential of spatial analysis for epidemiology research during COVID-19. Transparency and openness means that independent researchers can, with only modest efforts, verify findings and use different approaches as appropriate. Given the high stakes of the situation, it is essential that scientific findings, on which good policy depends, are as robust as possible; as the empirical example shows, reproducibility is one of the keys to ensure this.

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来源期刊
CiteScore
8.70
自引率
5.60%
发文量
40
期刊介绍: First in its specialty area and one of the most frequently cited publications in geography, Geographical Analysis has, since 1969, presented significant advances in geographical theory, model building, and quantitative methods to geographers and scholars in a wide spectrum of related fields. Traditionally, mathematical and nonmathematical articulations of geographical theory, and statements and discussions of the analytic paradigm are published in the journal. Spatial data analyses and spatial econometrics and statistics are strongly represented.
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