Cartenì Armando, Di Francesco Luigi, Martino Maria
Department of Engineering, University of Campania "Luigi Vanvitelli", via Roma 29, 81031 Aversa, Caserta, Italy.
Saf Sci. 2021 Jan;133:104999. doi: 10.1016/j.ssci.2020.104999. Epub 2020 Sep 14.
The Covid-19 pandemic has caused an unprecedented global crisis and led to a huge number of deaths, economic hardship and the disruption of everyday life. Measures to restrict accessibility adopted by many countries were a swift yet effective response to contain the spread of the virus. Within this topic, this paper aims to support policies and decision makers in defining the most appropriate strategies to manage the Covid-19 crisis. Precisely the correlation between positive Covid-19 cases and transport accessibility of an area was investigated through a multiple linear regression model. Estimation results show that transport accessibility was the variable that better explained the number of Covid-19 infections (about 40% in weight), meaning that the greater is the accessibility of a certain geographical area, the easier the virus reaches its population. Furthermore, other context variables were also significant, i.e. socio-economic, territorial and pollutant variables. Estimated findings show that accessibility, which is often used to measure the wealth of an area, becomes its worst enemy during a pandemic, providing to be the main vehicle of contagion among its citizens. These original results allow the definition of possible policies and/or best practices to better manage mobility restrictions. The quantitative estimates performed show that a possible and probably more sustainable policy for containing social interactions could be to apply lockdowns in proportion to the transport accessibility of the areas concerned, in the sense that the higher the accessibility, the tighter should be the mobility restriction policies adopted.
新冠疫情引发了一场前所未有的全球危机，导致大量死亡、经济困难以及日常生活的混乱。许多国家采取的限制可达性措施是遏制病毒传播的迅速而有效对策。在这个主题范围内，本文旨在支持政策制定者和决策者确定应对新冠危机的最合适策略。具体而言，通过多元线性回归模型研究了新冠确诊病例与某地区交通可达性之间的相关性。估计结果表明，交通可达性是能更好解释新冠感染病例数的变量（权重约为40%），这意味着某一地理区域的可达性越高，病毒就越容易传播至当地人群。此外，其他背景变量也具有显著性，即社会经济、地域和污染物变量。估计结果显示，可达性通常用于衡量一个地区的富裕程度，但在疫情期间却成为其最大的敌人，成为公民之间传播感染的主要媒介。这些原创性结果有助于确定更好管理出行限制的可能政策和/或最佳做法。所进行的定量估计表明，一种可能且或许更具可持续性的控制社交互动的政策，可能是根据相关地区的交通可达性按比例实施封锁，即可达性越高，所采取的出行限制政策就应越严格。
