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Geo-social gradients in predicted COVID-19 prevalence and severity in Great Britain: results from 2,266,235 users of the COVID-19 Symptoms Tracker app

Authors :
Bowyer, Ruth
Varsavsky, Thomas
Sudre, Carole H
Murray, Benjamin
Freidin, Maxim
Yarand, Darioush
Ganesh, Sajaysurya
Capdevila, Joan
Thompson, Ellen J
Bakker, Elco
Cardoso, M Jorge
Davies, Richard
Wolf, Jonathan
Spector, Tim D
Ourselin, Sebastien
Steves, Claire J
Menni, Cristina
Publication Year :
2020
Publisher :
Cold Spring Harbor Laboratory, 2020.

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 2,266,235 unique GB users of the COVID Symptom Tracker app, we find that COVID-19 prevalence and severity became rapidly distributed across the UK within a month of the WHO declaration of the pandemic, with significant evidence of “urban hot-spots”. We found a geo-social gradient associated with disease severity and prevalence suggesting resources should focus on urban areas and areas of higher deprivation. Our results demonstrate use of self-reported data to inform public health policy and resource allocation.

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....86d5aac5f3cb81e03cdbbafc8365eca3
Full Text :
https://doi.org/10.1101/2020.04.23.20076521