School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Medical Research Council Unit for Lifelong health and Ageing at UCL, Department of Population Science and Experimental Medicine, University College London, London, UK; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
Department of Computer Science and Applied Mathematics and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.
Lancet Digit Health. 2021 Sep;3(9):e577-e586. doi: 10.1016/S2589-7500(21)00115-1. Epub 2021 Jul 22.
BACKGROUND: Multiple voluntary surveillance platforms were developed across the world in response to the COVID-19 pandemic, providing a real-time understanding of population-based COVID-19 epidemiology. During this time, testing criteria broadened and health-care policies matured. We aimed to test whether there were consistent associations of symptoms with SARS-CoV-2 test status across three surveillance platforms in three countries (two platforms per country), during periods of testing and policy changes. METHODS: For this observational study, we used data of observations from three volunteer COVID-19 digital surveillance platforms (Carnegie Mellon University and University of Maryland Facebook COVID-19 Symptom Survey, ZOE COVID Symptom Study app, and the Corona Israel study) targeting communities in three countries (Israel, the UK, and the USA; two platforms per country). The study population included adult respondents (age 18-100 years at baseline) who were not health-care workers. We did logistic regression of self-reported symptoms on self-reported SARS-CoV-2 test status (positive or negative), adjusted for age and sex, in each of the study cohorts. We compared odds ratios (ORs) across platforms and countries, and we did meta-analyses assuming a random effects model. We also evaluated testing policy changes, COVID-19 incidence, and time scales of duration of symptoms and symptom-to-test time. FINDINGS: Between April 1 and July 31, 2020, 514 459 tests from over 10 million respondents were recorded in the six surveillance platform datasets. Anosmia-ageusia was the strongest, most consistent symptom associated with a positive COVID-19 test (robust aggregated rank one, meta-analysed random effects OR 16·96, 95% CI 13·13-21·92). Fever (rank two, 6·45, 4·25-9·81), shortness of breath (rank three, 4·69, 3·14-7·01), and cough (rank four, 4·29, 3·13-5·88) were also highly associated with test positivity. The association of symptoms with test status varied by duration of illness, timing of the test, and broader test criteria, as well as over time, by country, and by platform. INTERPRETATION: The strong association of anosmia-ageusia with self-reported positive SARS-CoV-2 test was consistently observed, supporting its validity as a reliable COVID-19 signal, regardless of the participatory surveillance platform, country, phase of illness, or testing policy. These findings show that associations between COVID-19 symptoms and test positivity ranked similarly in a wide range of scenarios. Anosmia, fever, and respiratory symptoms consistently had the strongest effect estimates and were the most appropriate empirical signals for symptom-based public health surveillance in areas with insufficient testing or benchmarking capacity. Collaborative syndromic surveillance could enhance real-time epidemiological investigations and public health utility globally. FUNDING: National Institutes of Health, National Institute for Health Research, Alzheimer's Society, Wellcome Trust, and Massachusetts Consortium on Pathogen Readiness.
背景:为应对 COVID-19 大流行,世界各地开发了多个自愿监测平台,实时了解基于人群的 COVID-19 流行病学情况。在此期间,检测标准放宽,医疗保健政策也不断成熟。我们旨在测试在三个国家(每个国家两个平台)的三个监测平台(卡内基梅隆大学和马里兰大学 Facebook COVID-19 症状调查、ZOE COVID 症状研究应用程序和以色列 Corona 研究)中,在检测和政策变化期间,症状与 SARS-CoV-2 检测结果之间是否存在一致的关联。
方法:在这项观察性研究中,我们使用了来自三个志愿者 COVID-19 数字监测平台(卡内基梅隆大学和马里兰大学 Facebook COVID-19 症状调查、ZOE COVID 症状研究应用程序和以色列 Corona 研究)的数据,这些平台针对三个国家(以色列、英国和美国;每个国家两个平台)的社区。研究人群包括年龄在 18-100 岁之间的非医护人员成年受访者。我们对每个研究队列中自我报告的症状与自我报告的 SARS-CoV-2 检测结果(阳性或阴性)进行了逻辑回归,调整了年龄和性别因素。我们比较了不同平台和国家的优势比(OR),并采用随机效应模型进行了荟萃分析。我们还评估了检测政策变化、COVID-19 发病率以及症状持续时间和症状检测时间的时间尺度。
结果:在 2020 年 4 月 1 日至 7 月 31 日期间,从超过 1000 万受访者中记录了 514459 次检测。嗅觉丧失和味觉丧失是与 COVID-19 检测呈阳性最强烈、最一致的症状(稳健的综合排名第一,荟萃分析的随机效应 OR 为 16.96,95%CI 为 13.13-21.92)。发热(排名第二,6.45,4.25-9.81)、呼吸急促(排名第三,4.69,3.14-7.01)和咳嗽(排名第四,4.29,3.13-5.88)也与检测结果呈高度相关。症状与检测结果的关联因疾病持续时间、检测时间和更广泛的检测标准以及随时间推移、国家和平台的不同而有所不同。
解释:嗅觉丧失和味觉丧失与自我报告的 SARS-CoV-2 检测阳性结果具有很强的关联,这一关联在不同的参与式监测平台、国家、疾病阶段或检测政策中均得到一致观察,支持了其作为 COVID-19 可靠信号的有效性。这些发现表明,COVID-19 症状与检测阳性结果之间的关联在广泛的情况下排名相似。嗅觉丧失、发热和呼吸症状始终具有最强的效应估计值,是在检测或基准能力不足的地区进行基于症状的公共卫生监测的最合适的经验信号。协作症状监测可以增强全球实时流行病学调查和公共卫生实用性。
资助:美国国立卫生研究院、英国国家健康研究所、阿尔茨海默病协会、惠康信托基金会和马萨诸塞州病原体准备联盟。
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