Detecting COVID-19 infection hotspots in England using large-scale self-reported data from a mobile application: a prospective, observational study

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BACKGROUND: As many countries seek to slow the spread of COVID-19 without reimposing national restrictions, it has become important to track the disease at a local level to identify areas in need of targeted intervention. METHODS: We performed modelling on longitudinal, self-reported data from users...

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Detalles Bibliográficos
Autores principales: Varsavsky, Thomas, Graham, Mark S., Canas, Liane S., Ganesh, Sajaysurya, Pujol, Joan Capdevila, Sudre, Carole H., Murray, Benjamin, Modat, Marc, Cardoso, M. Jorge, Astley, Christina M., Drew, David A, Nguyen, Long H., Fall, Tove, Gomez, Maria F, Franks, Paul W., Chan, Andrew T., Davies, Richard, Wolf, Jonathan, Steves, Claire J., Spector, Tim D., Ourselin, Sebastien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605586/
https://www.ncbi.nlm.nih.gov/pubmed/33140073
http://dx.doi.org/10.1101/2020.10.26.20219659

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605586/
https://www.ncbi.nlm.nih.gov/pubmed/33140073
http://dx.doi.org/10.1101/2020.10.26.20219659

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