TY - JOUR T1 - Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app JF - Thorax JO - Thorax SP - 723 LP - 725 DO - 10.1136/thoraxjnl-2020-215119 VL - 76 IS - 7 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 Y1 - 2021/07/01 UR - http://thorax.bmj.com/content/76/7/723.abstract N2 - 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. ER -