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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.
Lancet Digit Health. 2021 09; 3(9):e577-e586.LD

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.

Authors+Show Affiliations

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. Electronic address: c.sudre@ucl.ac.uk.Department of Computer Science and Applied Mathematics and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.Department of Computer Science and Applied Mathematics and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel; Pediatric Diabetes Unit, Ruth Rappaport Children's Hospital, Rambam Healthcare Campus, Haifa, Israel.Department of Computer Science and Applied Mathematics and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.ZOE Global, London, UK.ZOE Global, London, UK.ZOE Global, London, UK.Department of Computer Science and Applied Mathematics and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.Department of Twin Research and Genetic Epidemiology, King's College London, London, UK; ZOE Global, London, UK.Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA.Department of Computer Science and Applied Mathematics and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; AI Institute 3IA Côte d'Azur, Université Côte d'Azur, Nice, France.Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA; Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA; Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, USA.

Pub Type(s)

Journal Article
Observational Study
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

34305035

Citation

Sudre, Carole H., et al. "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." The Lancet. Digital Health, vol. 3, no. 9, 2021, pp. e577-e586.
Sudre CH, Keshet A, Graham MS, et al. 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. Lancet Digit Health. 2021;3(9):e577-e586.
Sudre, C. H., Keshet, A., Graham, M. S., Joshi, A. D., Shilo, S., Rossman, H., Murray, B., Molteni, E., Klaser, K., Canas, L. D., Antonelli, M., Nguyen, L. H., Drew, D. A., Modat, M., Pujol, J. C., Ganesh, S., Wolf, J., Meir, T., Chan, A. T., ... Astley, C. M. (2021). 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. The Lancet. Digital Health, 3(9), e577-e586. https://doi.org/10.1016/S2589-7500(21)00115-1
Sudre CH, et al. 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. Lancet Digit Health. 2021;3(9):e577-e586. PubMed PMID: 34305035.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - 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. AU - Sudre,Carole H, AU - Keshet,Ayya, AU - Graham,Mark S, AU - Joshi,Amit D, AU - Shilo,Smadar, AU - Rossman,Hagai, AU - Murray,Benjamin, AU - Molteni,Erika, AU - Klaser,Kerstin, AU - Canas,Liane D, AU - Antonelli,Michela, AU - Nguyen,Long H, AU - Drew,David A, AU - Modat,Marc, AU - Pujol,Joan Capdevila, AU - Ganesh,Sajaysurya, AU - Wolf,Jonathan, AU - Meir,Tomer, AU - Chan,Andrew T, AU - Steves,Claire J, AU - Spector,Tim D, AU - Brownstein,John S, AU - Segal,Eran, AU - Ourselin,Sebastien, AU - Astley,Christina M, Y1 - 2021/07/22/ PY - 2020/12/16/received PY - 2021/05/05/revised PY - 2021/06/04/accepted PY - 2021/7/27/pubmed PY - 2021/9/10/medline PY - 2021/7/26/entrez SP - e577 EP - e586 JF - The Lancet. Digital health JO - Lancet Digit Health VL - 3 IS - 9 N2 - 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. SN - 2589-7500 UR - https://www.unboundmedicine.com/medline/citation/34305035/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_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S2589-7500(21)00115-1 DB - PRIME DP - Unbound Medicine ER -