Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app. Issue 7 (29th December 2020)

• Record Type: Journal Article
• Authors: 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
• Is Part Of: Thorax. Volume 76:Issue 7(2021)
• Page Start: 723
• Page End: 725
• Publication Date: 2020-12-29
• Subjects: clinical epidemiology -- infection control; Chest -- Diseases -- Periodicals; Thorax; Chest -- Diseases; Periodicals; Periodicals; 617.54
• DOI: 10.1136/thoraxjnl-2020-215119
• Languages: English
• ISSNs: 0040-6376

Abstract

Abstract : 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.