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Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app

Understanding the geographical distribution of COVID-19 through the general population is key to the provision of adequate healthcare services. Using self-reported data from 1 960 242 unique users in Great Britain (GB) of the COVID-19 Symptom Study app, we estimated that, concurrent to the GB govern...

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Autores principales: Bowyer, Ruth C E, Varsavsky, Thomas, Thompson, Ellen J, Sudre, Carole H, Murray, Benjamin A K, Freidin, Maxim B, Yarand, Darioush, Ganesh, Sajaysurya, Capdevila, Joan, Bakker, Elco, Cardoso, M Jorge, Davies, Richard, Wolf, Jonathan, Spector, Tim D, Ourselin, Sebastien, Steves, Claire J, Menni, Cristina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8223682/
https://www.ncbi.nlm.nih.gov/pubmed/33376145
http://dx.doi.org/10.1136/thoraxjnl-2020-215119
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author Bowyer, Ruth C E
Varsavsky, Thomas
Thompson, Ellen J
Sudre, Carole H
Murray, Benjamin A K
Freidin, Maxim B
Yarand, Darioush
Ganesh, Sajaysurya
Capdevila, Joan
Bakker, Elco
Cardoso, M Jorge
Davies, Richard
Wolf, Jonathan
Spector, Tim D
Ourselin, Sebastien
Steves, Claire J
Menni, Cristina
author_facet Bowyer, Ruth C E
Varsavsky, Thomas
Thompson, Ellen J
Sudre, Carole H
Murray, Benjamin A K
Freidin, Maxim B
Yarand, Darioush
Ganesh, Sajaysurya
Capdevila, Joan
Bakker, Elco
Cardoso, M Jorge
Davies, Richard
Wolf, Jonathan
Spector, Tim D
Ourselin, Sebastien
Steves, Claire J
Menni, Cristina
author_sort Bowyer, Ruth C E
collection PubMed
description Understanding the geographical distribution of COVID-19 through the general population is key to the provision of adequate healthcare services. Using self-reported data from 1 960 242 unique users in Great Britain (GB) of the COVID-19 Symptom Study app, we estimated that, concurrent to the GB government sanctioning lockdown, COVID-19 was distributed across GB, with evidence of ‘urban hotspots’. We found a geo-social gradient associated with predicted disease prevalence suggesting urban areas and areas of higher deprivation are most affected. Our results demonstrate use of self-reported symptoms data to provide focus on geographical areas with identified risk factors.
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spelling pubmed-82236822021-07-09 Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app Bowyer, Ruth C E Varsavsky, Thomas Thompson, Ellen J Sudre, Carole H Murray, Benjamin A K Freidin, Maxim B Yarand, Darioush Ganesh, Sajaysurya Capdevila, Joan Bakker, Elco Cardoso, M Jorge Davies, Richard Wolf, Jonathan Spector, Tim D Ourselin, Sebastien Steves, Claire J Menni, Cristina Thorax Brief Communication Understanding the geographical distribution of COVID-19 through the general population is key to the provision of adequate healthcare services. Using self-reported data from 1 960 242 unique users in Great Britain (GB) of the COVID-19 Symptom Study app, we estimated that, concurrent to the GB government sanctioning lockdown, COVID-19 was distributed across GB, with evidence of ‘urban hotspots’. We found a geo-social gradient associated with predicted disease prevalence suggesting urban areas and areas of higher deprivation are most affected. Our results demonstrate use of self-reported symptoms data to provide focus on geographical areas with identified risk factors. BMJ Publishing Group 2021-07 2020-12-29 /pmc/articles/PMC8223682/ /pubmed/33376145 http://dx.doi.org/10.1136/thoraxjnl-2020-215119 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Brief Communication
Bowyer, Ruth C E
Varsavsky, Thomas
Thompson, Ellen J
Sudre, Carole H
Murray, Benjamin A K
Freidin, Maxim B
Yarand, Darioush
Ganesh, Sajaysurya
Capdevila, Joan
Bakker, Elco
Cardoso, M Jorge
Davies, Richard
Wolf, Jonathan
Spector, Tim D
Ourselin, Sebastien
Steves, Claire J
Menni, Cristina
Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app
title Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app
title_full Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app
title_fullStr Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app
title_full_unstemmed Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app
title_short Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app
title_sort geo-social gradients in predicted covid-19 prevalence in great britain: results from 1 960 242 users of the covid-19 symptoms study app
topic Brief Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8223682/
https://www.ncbi.nlm.nih.gov/pubmed/33376145
http://dx.doi.org/10.1136/thoraxjnl-2020-215119
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