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

被引：10

作者：

Bowyer, Ruth C. E. ^{[1
]}

Varsavsky, Thomas ^{[2
]}

Thompson, Ellen J. ^{[1
]}

Sudre, Carole H. ^{[2
,3
]}

Murray, Benjamin A. K. ^{[2
]}

Freidin, Maxim B. ^{[1
]}

Yarand, Darioush ^{[1
]}

Ganesh, Sajaysurya ^{[4
]}

Capdevila, Joan ^{[4
]}

Bakker, Elco ^{[4
]}

Cardoso, M. Jorge ^{[2
]}

Davies, Richard ^{[4
]}

Wolf, Jonathan ^{[4
]}

Spector, Tim D. ^{[1
]}

Ourselin, Sebastien ^{[2
]}

Steves, Claire J. ^{[1
]}

Menni, Cristina ^{[1
]}

机构：

[1] Kings Coll London, Twin Res, London, England

[2] Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England

[3] UCL, MRC Unit Lifelong Hlth & Ageing, London, England

[4] Zoe Global Ltd, London, England

来源：

THORAX | 2021年 / 76卷 / 07期

基金：

英国医学研究理事会; 英国惠康基金; 英国工程与自然科学研究理事会;

关键词：

tobacco and the lung; viral infection; respiratory infection; clinical epidemiology;

D O I：

10.1136/thoraxjnl-2020-215119

中图分类号：

R56 [呼吸系及胸部疾病];

学科分类号：

摘要：

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.

引用

页码：723 / 725

页数：3

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