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
Twin Research, King's College London, London, UK.
School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
Thorax. 2021 Jul;76(7):723-725. doi: 10.1136/thoraxjnl-2020-215119. Epub 2020 Dec 29.
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 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.
通过普通人群了解新冠病毒病（COVID-19）的地理分布是提供充足医疗服务的关键。利用来自英国（GB）1960242名独特用户的自我报告数据，我们估计，在英国政府批准封锁的同时，COVID-19已在英国各地传播，并有“城市热点”的证据。我们发现了与预测疾病患病率相关的地理社会梯度，表明城市地区和贫困程度较高的地区受影响最大。我们的结果表明，利用自我报告的症状数据可以关注那些已确定风险因素的地理区域。
