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Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing.
Nature Human Behaviour ( IF 21.4 ) Pub Date : 2020-08-26 , DOI: 10.1038/s41562-020-00944-2
William E Allen 1, 2, 3 , Han Altae-Tran 1, 3, 4 , James Briggs 1, 3, 5 , Xin Jin 1, 2, 3 , Glen McGee 1, 6 , Andy Shi 1, 6 , Rumya Raghavan 1, 3, 7 , Mireille Kamariza 1, 2, 3 , Nicole Nova 1, 8 , Albert Pereta 1 , Chris Danford 1 , Amine Kamel 1 , Patrik Gothe 1 , Evrhet Milam 1 , Jean Aurambault 1 , Thorben Primke 1 , Weijie Li 1 , Josh Inkenbrandt 1 , Tuan Huynh 1 , Evan Chen 1 , Christina Lee 1 , Michael Croatto 1 , Helen Bentley 1 , Wendy Lu 1 , Robert Murray 1 , Mark Travassos 1, 9 , Brent A Coull 6 , John Openshaw 1, 10 , Casey S Greene 1, 11 , Ophir Shalem 1, 12 , Gary King 1, 13 , Ryan Probasco 1 , David R Cheng 1 , Ben Silbermann 1 , Feng Zhang 1, 3, 4, 14, 15, 16 , Xihong Lin 1, 3, 6, 17
Affiliation  

Despite the widespread implementation of public health measures, coronavirus disease 2019 (COVID-19) continues to spread in the United States. To facilitate an agile response to the pandemic, we developed How We Feel, a web and mobile application that collects longitudinal self-reported survey responses on health, behaviour and demographics. Here, we report results from over 500,000 users in the United States from 2 April 2020 to 12 May 2020. We show that self-reported surveys can be used to build predictive models to identify likely COVID-19-positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation; show a variety of exposure, occupational and demographic risk factors for COVID-19 beyond symptoms; reveal factors for which users have been SARS-CoV-2 PCR tested; and highlight the temporal dynamics of symptoms and self-isolation behaviour. These results highlight the utility of collecting a diverse set of symptomatic, demographic, exposure and behavioural self-reported data to fight the COVID-19 pandemic.



中文翻译:


COVID-19 症状、行为和测试的人口规模纵向映射。



尽管广泛实施了公共卫生措施,2019 年冠状病毒病 (COVID-19) 仍在美国继续传播。为了促进对这一流行病的敏捷反应,我们开发了 How We Feel,这是一个网络和移动应用程序,用于收集有关健康、行为和人口统计的纵向自我报告调查答复。在此,我们报告了 2020 年 4 月 2 日至 2020 年 5 月 12 日期间美国超过 500,000 名用户的结果。我们表明,自我报告的调查可用于构建预测模型,以识别可能的 COVID-19 阳性个体。我们在用户中发现无症状或症状前表现的证据;显示除症状外的各种接触、职业和人口统计风险因素的 COVID-19;揭示用户接受 SARS-CoV-2 PCR 测试的因素;并强调症状和自我隔离行为的时间动态。这些结果凸显了收集各种症状、人口统计、暴露和行为自我报告数据来对抗 COVID-19 大流行的效用。

更新日期:2020-08-26
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