Gibbs Hamish, Waterlow Naomi R, Cheshire James, Danon Leon, Liu Yang, Grundy Chris, Kucharski Adam J, Eggo Rosalind M
Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Department of Geography, University College London, London, United Kingdom.
medRxiv. 2022 Aug 12:2021.06.22.21259336. doi: 10.1101/2021.06.22.21259336.
Mobility data have demonstrated major changes in human movement patterns in response to COVID-19 and associated interventions in many countries. This can involve sub-national redistribution, short-term relocations as well as international migration. In this paper, we combine detailed location data from Facebook measuring the location of approximately 6 million daily active Facebook users in 5km tiles in the UK with census-derived population estimates to measure population mobility and redistribution. We provide time-varying population estimates and assess spatial population changes with respect to population density and four key reference dates in 2020 (First lockdown, End of term, Beginning of term, Christmas). We also show how population estimates derived from the distribution of Facebook users vary compared to mid-2020 small area population estimates by the UK national statistics agencies. We estimate that between March 2020 and March 2021, the total population of the UK declined and we identify important spatial variations in this population change, showing that low-density areas have experienced lower population decreases than urban areas. We estimate that, for the top 10% highest population tiles, the population has decreased by 6.6%. Further, we provide evidence that geographic redistributions of population within the UK coincide with dates of non-pharmaceutical interventions including lockdowns and movement restrictions, as well as seasonal patterns of migration around holiday dates. The methods used in this study reveal significant changes in population distribution at high spatial and temporal resolutions that have not previously been quantified by available demographic surveys in the UK. We found early indicators of potential longer-term changes in the population distribution of the UK although it is not clear if these changes may persist after the COVID-19 pandemic.
移动性数据表明,在许多国家,人类的移动模式因新冠疫情及相关干预措施而发生了重大变化。这可能涉及国家以下层面的重新分布、短期迁移以及国际移民。在本文中,我们将来自脸书的详细位置数据(测量英国5公里网格内约600万每日活跃脸书用户的位置)与人口普查得出的人口估计数相结合,以衡量人口流动性和重新分布情况。我们提供随时间变化的人口估计数,并根据人口密度和2020年的四个关键参考日期(首次封锁、学期结束、学期开始、圣诞节)评估空间人口变化。我们还展示了从脸书用户分布得出的人口估计数与英国国家统计机构2020年年中小区人口估计数相比有何不同。我们估计,在2020年3月至2021年3月期间,英国总人口有所下降,并且我们确定了这一人口变化中的重要空间差异,表明低密度地区的人口减少幅度低于城市地区。我们估计,对于人口最多的前10%的网格,人口减少了6.6%。此外,我们提供的证据表明,英国境内人口的地理重新分布与包括封锁和行动限制在内的非药物干预措施的日期以及节假日前后的季节性迁移模式相吻合。本研究中使用的方法揭示了在高空间和时间分辨率下人口分布的显著变化,而英国现有的人口统计调查此前并未对这些变化进行量化。我们发现了英国人口分布可能出现长期变化的早期迹象,不过目前尚不清楚这些变化在新冠疫情之后是否会持续。