Real-time tracking of self-reported symptoms to predict potential COVID-19
Date
2020-05-11Author
Menni, Cristina
Valdes, Ana M.
Freidin, Maxim B.
Sudre, Carole H.
Nguyen, Long H.
Drew, David A.
Ganesh, Sajaysurya
Varsavsky, Thomas
Cardoso, M. Jorge
El-Sayed Moustafa, Julia S.
Visconti, Alessia
Hysi, Pirro
Bowyer, Ruth C.E.
Mangino, Massimo
Falchi, Mario
Wolf, Jonathan
Ourselin, Sebastien
Chan, Andrew T.
Steves, Claire J.
Spector, Tim D.
Metadata
Show full item record
Documentos PDF
Summary in foreign language
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.
Palabras clave
Síntomas autoinformadosLink to resource
https://www.nature.com/articles/s41591-020-0916-2Collections
Estadísticas Google Analytics
Comments
Respuesta Comentario Repositorio Expeditio
Gracias por tomarse el tiempo para darnos su opinión.