Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app
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Abstract
Understanding the geographical distribution of COVID-19 through the general population is key to the provision of adequate healthcare services. Using self-reported data from 1 960 242 unique users in Great Britain (GB) of the COVID-19 Symptom Study app, we estimated that, concurrent to the GB government sanctioning lockdown, COVID-19 was distributed across GB, with evidence of ‘urban hotspots’. We found a geo-social gradient associated with predicted disease prevalence suggesting urban areas and areas of higher deprivation are most affected. Our results demonstrate use of self-reported symptoms data to provide focus on geographical areas with identified risk factors.
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Previous work has shown that data from the app is able to produce estimates of population-level disease prevalence that agree well with surveys with random, representative designs, suggesting that behavioural issues are not substantially biasing the app population.
“Previous work has shown that data from our app is able to produce estimates of population-level disease prevalence that agree well with surveys with random, representative designs,18, 28 suggesting that behavioural issues are not substantially biasing our app population.”
From Vaccine side-effects and SARS-CoV-2 infection after vaccination in users of the COVID Symptom Study app in the UK: a prospective observational study (2021) · cites this paper as [28]
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Cites
Rapid implementation of mobile technology for real-time epidemiology of COVID-19
Drew, D. A., Nguyen, L. H., Steves, C. J., Menni, C., Freydin, M., Varsavsky, T., Sudre, C. H., Cardoso, M. J., Ourselin, S., Wolf, J., et al. (2020) · Science · doi:10.1126/science.abc0473 · Cited by 389 · see citing works
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Menni, C., Klaser, K., May, A., Polidori, L., Capdevila, J., Louca, P., Sudre, C. H., Nguyen, L. H., Drew, D. A., Merino, J., et al. (2021) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(21)00224-3 · Cited by 1,031 · see citing works
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- Authors
- Bowyer, R. C. E., Varsavsky, T., Thompson, E. J., Sudre, C. H., Murray, B. A. K., Freidin, M. B., Yarand, D., Ganesh, S., Capdevila, J., Bakker, E., Cardoso, M. J., Davies, R., Wolf, J., Spector, T. D., Ourselin, S., Steves, C. J., & Menni, C.
- Affiliations
- King's College London (GB)
- ZOE (United Kingdom) (GB)
- Corresponding author
- Menni, Cristina
- ORCID
- Venue
- Thorax
- Publisher
- BMJ
- Published
- 2020-12-29
- Volume
- 76
- Issue
- 7
- Pages
- 723-725
- ISSN
- 0040-6376 (ISSN-L)
- 1468-3296
- PMC
- PMC8223682
- OpenAlex
- W3113477596
- Cited by
- 24
- References
- 1
- Citations by year
- 2023: 2 · 2022: 3 · 2021: 12 · 2020: 7
- FWCI
- 0.95
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Thorax (publishedVersion, cc-by)
- medRxiv (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- Queen Mary Research Online (Queen Mary University of London) (submittedVersion, cc-by)
- Funders
- Wellcome Trust (212904/Z/18/Z, WT203148/Z/16/Z, WT213038/Z/18/Z)
- Zoe Global Limited
- Alzheimer Society (AS-JF-17-011)
- Chronic Disease Research Foundation
- Medical Research Council (AIMHY MR/M016560/1)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Epidemiology › Data-Driven Disease Surveillance
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Keywords
- COVID-19 pandemic, disease prevalence, urban hotspots, socioeconomic deprivation, self-reported symptoms, mobile health, lockdown, spatial distribution of disease, Great Britain
- MeSH terms
- COVID-19, Adult, Female, United Kingdom, Humans, Male, Mass Screening, Middle Aged, Pneumonia, Viral, Risk Factors, Prevalence, Self Report, Mobile Applications
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