PT  - JOURNAL ARTICLE
AU  - Ruth C E Bowyer
AU  - Thomas Varsavsky
AU  - Ellen J Thompson
AU  - Carole H Sudre
AU  - Benjamin A K Murray
AU  - Maxim B Freidin
AU  - Darioush Yarand
AU  - Sajaysurya Ganesh
AU  - Joan Capdevila
AU  - Elco Bakker
AU  - M Jorge Cardoso
AU  - Richard Davies
AU  - Jonathan Wolf
AU  - Tim D Spector
AU  - Sebastien Ourselin
AU  - Claire J Steves
AU  - Cristina Menni
TI  - Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app
AID  - 10.1136/thoraxjnl-2020-215119
DP  - 2021 Jul 01
TA  - Thorax
PG  - 723--725
VI  - 76
IP  - 7
4099  - http://thorax.bmj.com/content/76/7/723.short
4100  - http://thorax.bmj.com/content/76/7/723.full
SO  - Thorax2021 Jul 01; 76
AB  - 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.