24
views
0
recommends
+1 Recommend
3 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found

      Anosmia, ageusia, and other COVID-19-like symptoms in association with a positive SARS-CoV-2 test, across six national digital surveillance platforms: an observational study

      research-article
      , PhD a , b , c , , * , , MSc d , , , PhD a , , PhD e , , MD d , f , , PhD d , , MSc a , , PhDi a , , MSc a , , PhD a , , PhD a , , MD e , , PhD e , , PhD a , , PhD h , , MSc h , , PhD h , , PhD d , , Prof, MD e , , PhD g , , Prof, PhD g , h , , Prof, PhD i , , Prof, PhD d , , Prof, PhD a , l , , MD i , j , k
      The Lancet. Digital Health
      The Author(s). Published by Elsevier Ltd.

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          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.

          Related collections

          Most cited references26

          • Record: found
          • Abstract: found
          • Article: not found

          Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe

          Following the detection of the new coronavirus1 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics of coronavirus disease 2019 (COVID-19). In response, many European countries have implemented non-pharmaceutical interventions, such as the closure of schools and national lockdowns. Here we study the effect of major interventions across 11 European countries for the period from the start of the COVID-19 epidemics in February 2020 until 4 May 2020, when lockdowns started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks previously, allowing for the time lag between infection and death. We use partial pooling of information between countries, with both individual and shared effects on the time-varying reproduction number (Rt). Pooling allows for more information to be used, helps to overcome idiosyncrasies in the data and enables more-timely estimates. Our model relies on fixed estimates of some epidemiological parameters (such as the infection fatality rate), does not include importation or subnational variation and assumes that changes in Rt are an immediate response to interventions rather than gradual changes in behaviour. Amidst the ongoing pandemic, we rely on death data that are incomplete, show systematic biases in reporting and are subject to future consolidation. We estimate that-for all of the countries we consider here-current interventions have been sufficient to drive Rt below 1 (probability Rt < 1.0 is greater than 99%) and achieve control of the epidemic. We estimate that across all 11 countries combined, between 12 and 15 million individuals were infected with SARS-CoV-2 up to 4 May 2020, representing between 3.2% and 4.0% of the population. Our results show that major non-pharmaceutical interventions-and lockdowns in particular-have had a large effect on reducing transmission. Continued intervention should be considered to keep transmission of SARS-CoV-2 under control.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Mild or Moderate Covid-19

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Real-time tracking of self-reported symptoms to predict potential COVID-19

              A total of 2,618,862 participants reported their potential symptoms of COVID-19 on a smartphone-based app. Among the 18,401 who had undergone a SARS-CoV-2 test, the proportion of participants who reported loss of smell and taste was higher in those with a positive test result (4,668 of 7,178 individuals; 65.03%) than in those with a negative test result (2,436 of 11,223 participants; 21.71%) (odds ratio = 6.74; 95% confidence interval = 6.31–7.21). A model combining symptoms to predict probable infection was applied to the data from all app users who reported symptoms (805,753) and predicted that 140,312 (17.42%) participants are likely to have COVID-19.
                Bookmark

                Author and article information

                Journal
                Lancet Digit Health
                Lancet Digit Health
                The Lancet. Digital Health
                The Author(s). Published by Elsevier Ltd.
                2589-7500
                22 July 2021
                22 July 2021
                Affiliations
                [a ]School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
                [b ]Medical Research Council Unit for Lifelong health and Ageing at UCL, Department of Population Science and Experimental Medicine, University College London, London, UK
                [c ]Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
                [d ]Department of Computer Science and Applied Mathematics and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
                [e ]Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
                [f ]Pediatric Diabetes Unit, Ruth Rappaport Children's Hospital, Rambam Healthcare Campus, Haifa, Israel
                [g ]Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
                [h ]ZOE Global, London, UK
                [i ]Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA
                [j ]Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA
                [k ]Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, USA
                [l ]AI Institute 3IA Côte d'Azur, Université Côte d'Azur, Nice, France
                Author notes
                [* ]Correspondence to: Dr Carole H Sudre, Medical Research Council Unit for Lifelong Health and Ageing at UCL, University College London, London WC1E 6DH, UK
                [†]

                Contributed equally

                Article
                S2589-7500(21)00115-1
                10.1016/S2589-7500(21)00115-1
                8297994
                34305035
                94f38723-1d50-48c7-8cb4-453b73a03f37
                © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                Categories
                Articles

                Comments

                Comment on this article