PT - JOURNAL ARTICLE AU - Bowyer, Ruth C E AU - Varsavsky, Thomas AU - Thompson, Ellen J AU - Sudre, Carole H AU - Murray, Benjamin A K AU - Freidin, Maxim B AU - Yarand, Darioush AU - Ganesh, Sajaysurya AU - Capdevila, Joan AU - Bakker, Elco AU - Cardoso, M Jorge AU - Davies, Richard AU - Wolf, Jonathan AU - Spector, Tim D AU - Ourselin, Sebastien AU - Steves, Claire J AU - Menni, Cristina 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.