ABSTRACT

The spread of Covid-19 is a global concern, especially in the most developed countries where the rapid spread of the virus has taken governments by surprise. Adopting a spatial approach to this issue, we identify the spatial factors that help explain why some areas are hit harder than others, based on the Italian example (with the Lombardy region as the epicentre in Europe). Our analysis combines an autoregressive spatial model and a bivariate spatial autocorrelation from a pool of data collected from the Italian provinces to propose a real-time analysis of the spread and concentration of the virus. The findings suggest that the most globally connected areas are also the worst hit, and that the implementation of a lockdown at the beginning of March 2020 was a crucial and effective approach to slowing the spread of the virus further.

摘要

Covid-19 的传播是全球关注的问题，特别是在最发达国家，病毒的迅速传播使政府措手不及。针对这个问题采用空间方法，我们根据意大利的例子（伦巴第地区作为欧洲的震中）确定了有助于解释为什么某些地区比其他地区受到的打击更大的空间因素。我们的分析结合了自回归空间模型和来自意大利各省收集的数据池的双变量空间自相关，以提出对病毒传播和浓度的实时分析。调查结果表明，全球联系最紧密的地区也受到了最严重的打击，在 2020 年 3 月初实施封锁是进一步减缓病毒传播的关键而有效的方法。