Institut de Physique des 2 Infinis (IP2I), CNRS/IN2P3, UMR5822, 69622, Villeurbanne, France.
Université de Lyon, Université Claude Bernard Lyon 1, 69001, Lyon, France.
Sci Rep. 2021 Feb 18;11(1):4150. doi: 10.1038/s41598-021-83441-4.
We employ the Google and Apple mobility data to identify, quantify and classify different degrees of social distancing and characterise their imprint on the first wave of the COVID-19 pandemic in Europe and in the United States. We identify the period of enacted social distancing via Google and Apple data, independently from the political decisions. Our analysis allows us to classify different shades of social distancing measures for the first wave of the pandemic. We observe a strong decrease in the infection rate occurring two to five weeks after the onset of mobility reduction. A universal time scale emerges, after which social distancing shows its impact. We further provide an actual measure of the impact of social distancing for each region, showing that the effect amounts to a reduction by 20-40% in the infection rate in Europe and 30-70% in the US.
我们利用谷歌和苹果的移动数据来识别、量化和分类不同程度的社交隔离,并描述其对欧洲和美国 COVID-19 大流行第一波疫情的影响。我们通过谷歌和苹果的数据来确定实施社交隔离的时期,而这些数据与政治决策无关。我们的分析允许我们对大流行第一波疫情的不同程度的社交隔离措施进行分类。我们观察到,在移动性降低开始后的两到五周内,感染率呈大幅下降趋势。在这个时间尺度之后,社交隔离措施开始显现其效果。我们进一步为每个地区提供了社交隔离措施影响的实际衡量标准,结果表明,欧洲地区的感染率降低了 20-40%,美国地区降低了 30-70%。