Knowledge barriers in a national symptomatic-COVID-19 testing programme.


Journal

PLOS global public health
ISSN: 2767-3375
Titre abrégé: PLOS Glob Public Health
Pays: United States
ID NLM: 9918283779606676

Informations de publication

Date de publication:
2022
Historique:
received: 07 06 2021
accepted: 24 11 2021
entrez: 24 3 2023
pubmed: 19 1 2022
medline: 19 1 2022
Statut: epublish

Résumé

Symptomatic testing programmes are crucial to the COVID-19 pandemic response. We sought to examine United Kingdom (UK) testing rates amongst individuals with test-qualifying symptoms, and factors associated with not testing. We analysed a cohort of untested symptomatic app users (N = 1,237), nested in the Zoe COVID Symptom Study (Zoe, N = 4,394,948); and symptomatic respondents who wanted, but did not have a test (N = 1,956), drawn from a University of Maryland survey administered to Facebook users (The Global COVID-19 Trends and Impact Survey [CTIS], N = 775,746). The proportion tested among individuals with incident test-qualifying symptoms rose from ~20% to ~75% from April to December 2020 in Zoe. Testing was lower with one vs more symptoms (72.9% vs 84.6% p<0.001), or short vs long symptom duration (69.9% vs 85.4% p<0.001). 40.4% of survey respondents did not identify all three test-qualifying symptoms. Symptom identification decreased for every decade older (OR = 0.908 [95% CI 0.883-0.933]). Amongst symptomatic UMD-CTIS respondents who wanted but did not have a test, not knowing where to go was the most cited factor (32.4%); this increased for each decade older (OR = 1.207 [1.129-1.292]) and for every 4-years fewer in education (OR = 0.685 [0.599-0.783]). Despite current UK messaging on COVID-19 testing, there is a knowledge gap about when and where to test, and this may be contributing to the ~25% testing gap. Risk factors, including older age and less education, highlight potential opportunities to tailor public health messages. The testing gap may be ever larger in countries that do not have extensive, free testing, as the UK does.

Identifiants

pubmed: 36962066
doi: 10.1371/journal.pgph.0000028
pii: PGPH-D-21-00099
pmc: PMC10022193
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e0000028

Informations de copyright

Copyright: © 2022 Graham et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have read the journal’s policy and the authors of this manuscript have the following competing interests. AM, JCP, CH, JW are employees of Zoe Global Ltd. TDS is a consultant to Zoe Global Ltd. DAD and ATC previously served as investigators on a clinical trial of diet and lifestyle using a separate smartphone application that was supported by Zoe Global. ATC reports grants from Massachusetts Consortium on Pathogen Readiness, during the conduct of the study; personal fees from Pfizer Inc., personal fees from Boehringer Ingelheim, personal fees from Bayer Pharma AG, outside the submitted work. DAD reports grants from National Institutes of Health, grants from MassCPR, grants from American Gastroenterological Association during the conduct of the study. All other authors have declared that no competing interests exist.

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Auteurs

Mark S Graham (MS)

School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.

Anna May (A)

Zoe Global Limited, London, United Kingdom.

Thomas Varsavsky (T)

School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.

Carole H Sudre (CH)

School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Department of Population Science and Experimental Medicine, MRC Unit for Lifelong Health and Ageing, University College London, London, United Kingdom.
Department of Computer Science, Centre for Medical Image Computing, University College London, London, United Kingdom.

Benjamin Murray (B)

School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.

Kerstin Kläser (K)

School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.

Michela Antonelli (M)

School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.

Liane S Canas (LS)

School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.

Erika Molteni (E)

School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.

Marc Modat (M)

School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.

M Jorge Cardoso (MJ)

School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.

David A Drew (DA)

Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America.

Long H Nguyen (LH)

Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America.

Benjamin Rader (B)

Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, United States of America.
Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States of America.

Christina Hu (C)

Zoe Global Limited, London, United Kingdom.

Joan Capdevila (J)

Zoe Global Limited, London, United Kingdom.

Alexander Hammers (A)

School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, London, United Kingdom.

Andrew T Chan (AT)

Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America.

Jonathan Wolf (J)

Zoe Global Limited, London, United Kingdom.

John S Brownstein (JS)

Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, United States of America.

Tim D Spector (TD)

Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom.

Sebastien Ourselin (S)

School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.

Claire J Steves (CJ)

Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom.

Christina M Astley (CM)

Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, United States of America.
Division of Endocrinology, Boston Children's Hospital, Boston, MA, United States of America.
Broad Institute of Harvard and MIT, Cambridge, MA, United States of America.

Classifications MeSH