De Lellis Pietro, Ruiz Marín Manuel, Porfiri Maurizio
Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy.
Department of Quantitative Methods, Law and Modern Languages, Technical University of Cartagena, 30201 Cartagena, Murcia Spain.
Eur Phys J Spec Top. 2022;231(9):1635-1643. doi: 10.1140/epjs/s11734-021-00299-3. Epub 2021 Oct 28.
In the media, a prevalent narrative is that the incumbent United States President Donald J. Trump lost the 2020 elections because of the way he handled the COVID-19 pandemic. Quantitative evidence to support this narrative is, however, limited. We put forward a spatial, information-theoretic approach to critically examine the link between voting behavior and COVID-19 incidence in the 2020 presidential elections. The approach overcomes classical limitations of traditional regression analysis, where it does not require an underlying mathematical model and it can capture nonlinear interactions. From the analysis of county-level data, we uncovered a robust association between voting behavior and prevalence of COVID-19 cases. Surprisingly, such an association points in the opposite direction from the accepted narrative: in counties that experienced less COVID-19 cases, the incumbent President lost more ground to his opponent, now President Joseph R. Biden Jr. A tenable explanation of this observation is the different attitude of liberal and conservative voters toward the pandemic, which led to more COVID-19 spreading in counties with a larger share of republican voters.
在媒体上，一种普遍的说法是，现任美国总统唐纳德·J·特朗普输掉2020年大选是因为他应对新冠疫情的方式。然而，支持这一说法的量化证据有限。我们提出一种基于空间信息论的方法，以批判性地审视2020年总统选举中投票行为与新冠疫情发病率之间的联系。该方法克服了传统回归分析的经典局限性，它不需要潜在的数学模型，并且能够捕捉非线性相互作用。通过对县级数据的分析，我们发现投票行为与新冠病例流行率之间存在紧密关联。令人惊讶的是，这种关联指向的方向与普遍说法相反：在新冠病例较少的县，现任总统输给对手、即现任总统小约瑟夫·R·拜登的幅度更大。对这一观察结果的一个合理的解释是，自由派和保守派选民对疫情的态度不同，这导致在共和党选民占比更大的县，新冠疫情传播得更厉害。
