This paper has the goal of evaluating how changes in mobility has affected the infection spread of Covid-19 throughout the 2020-2021 years. However, identifying a "clean" causal relation is not an easy task due to a high number of non-observable (behavioral) effects. We suggest the usage of Google Trends and News-based indexes as controls for some of these behavioral effects and we find that a 1\% increase in residential mobility (i.e. a reduction in overall mobility) have significant impacts for reducing both Covid-19 cases (at least 3.02\% on a one-month horizon) and deaths (at least 2.43\% at the two-weeks horizon) over the 2020-2021 sample. We also evaluate the effects of mobility on Covid-19 spread on the restricted sample (only 2020) where vaccines were not available. The results of diminishing mobility over cases and deaths on the restricted sample are still observable (with similar magnitudes in terms of residential mobility) and cumulative higher, as the effects of restricting workplace mobility turns to be also significant: a 1\% decrease in workplace mobility diminishes cases around 1\% and deaths around 2\%.
翻译:本文的目的是评估在2020-2021年期间流动的变化如何影响Covid-19感染的传播;然而,由于大量不可观察(行为)效应,确定“清洁”因果关系并非一项容易的任务;我们建议使用谷歌趋势和基于新闻的指数来控制其中一些行为效应,我们发现,住宅流动性的增加(即总体流动性的减少)对减少Covid-19病例(在一个月的地平线上至少为3.02 ⁇ )和减少2020-2021年样本中死亡(在两周的地平线上至少为2.43 ⁇ )产生重大影响;我们还评估了在缺乏疫苗的有限样本中(仅在2020年)移动对Covid-19扩散的影响;在有限样本中减少案件流动性和死亡的结果仍然可以观察(在居住流动性方面同样严重)和累积性提高,因为限制工作场所流动性的影响也变得相当显著:工作场所流动性减少1 ⁇ 减少,死亡病例在1 ⁇ 左右。