Cargando…
Population disruption: estimating changes in population distribution of the UK during the COVID-19 pandemic
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 f...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8240694/ https://www.ncbi.nlm.nih.gov/pubmed/34189539 http://dx.doi.org/10.1101/2021.06.22.21259336 |
_version_ | 1783715257474088960 |
---|---|
author | Gibbs, Hamish Waterlow, Naomi R Cheshire, James Danon, Leon Liu, Yang Grundy, Chris Kucharski, Adam J. Eggo, Rosalind M. |
author_facet | Gibbs, Hamish Waterlow, Naomi R Cheshire, James Danon, Leon Liu, Yang Grundy, Chris Kucharski, Adam J. Eggo, Rosalind M. |
author_sort | Gibbs, Hamish |
collection | PubMed |
description | 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(2) 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. |
format | Online Article Text |
id | pubmed-8240694 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-82406942022-12-15 Population disruption: estimating changes in population distribution of the UK during the COVID-19 pandemic Gibbs, Hamish Waterlow, Naomi R Cheshire, James Danon, Leon Liu, Yang Grundy, Chris Kucharski, Adam J. Eggo, Rosalind M. medRxiv Article 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(2) 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. Cold Spring Harbor Laboratory 2022-08-12 /pmc/articles/PMC8240694/ /pubmed/34189539 http://dx.doi.org/10.1101/2021.06.22.21259336 Text en https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Gibbs, Hamish Waterlow, Naomi R Cheshire, James Danon, Leon Liu, Yang Grundy, Chris Kucharski, Adam J. Eggo, Rosalind M. Population disruption: estimating changes in population distribution of the UK during the COVID-19 pandemic |
title | Population disruption: estimating changes in population distribution of the UK during the COVID-19 pandemic |
title_full | Population disruption: estimating changes in population distribution of the UK during the COVID-19 pandemic |
title_fullStr | Population disruption: estimating changes in population distribution of the UK during the COVID-19 pandemic |
title_full_unstemmed | Population disruption: estimating changes in population distribution of the UK during the COVID-19 pandemic |
title_short | Population disruption: estimating changes in population distribution of the UK during the COVID-19 pandemic |
title_sort | population disruption: estimating changes in population distribution of the uk during the covid-19 pandemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8240694/ https://www.ncbi.nlm.nih.gov/pubmed/34189539 http://dx.doi.org/10.1101/2021.06.22.21259336 |
work_keys_str_mv | AT gibbshamish populationdisruptionestimatingchangesinpopulationdistributionoftheukduringthecovid19pandemic AT waterlownaomir populationdisruptionestimatingchangesinpopulationdistributionoftheukduringthecovid19pandemic AT cheshirejames populationdisruptionestimatingchangesinpopulationdistributionoftheukduringthecovid19pandemic AT danonleon populationdisruptionestimatingchangesinpopulationdistributionoftheukduringthecovid19pandemic AT liuyang populationdisruptionestimatingchangesinpopulationdistributionoftheukduringthecovid19pandemic AT grundychris populationdisruptionestimatingchangesinpopulationdistributionoftheukduringthecovid19pandemic AT kucharskiadamj populationdisruptionestimatingchangesinpopulationdistributionoftheukduringthecovid19pandemic AT populationdisruptionestimatingchangesinpopulationdistributionoftheukduringthecovid19pandemic AT eggorosalindm populationdisruptionestimatingchangesinpopulationdistributionoftheukduringthecovid19pandemic |