Nature Communications (Apr 2022)
App-based COVID-19 syndromic surveillance and prediction of hospital admissions in COVID Symptom Study Sweden
- Beatrice Kennedy,
- Hugo Fitipaldi,
- Ulf Hammar,
- Marlena Maziarz,
- Neli Tsereteli,
- Nikolay Oskolkov,
- Georgios Varotsis,
- Camilla A. Franks,
- Diem Nguyen,
- Lampros Spiliopoulos,
- Hans-Olov Adami,
- Jonas Björk,
- Stefan Engblom,
- Katja Fall,
- Anna Grimby-Ekman,
- Jan-Eric Litton,
- Mats Martinell,
- Anna Oudin,
- Torbjörn Sjöström,
- Toomas Timpka,
- Carole H. Sudre,
- Mark S. Graham,
- Julien Lavigne du Cadet,
- Andrew T. Chan,
- Richard Davies,
- Sajaysurya Ganesh,
- Anna May,
- Sébastien Ourselin,
- Joan Capdevila Pujol,
- Somesh Selvachandran,
- Jonathan Wolf,
- Tim D. Spector,
- Claire J. Steves,
- Maria F. Gomez,
- Paul W. Franks,
- Tove Fall
Affiliations
- Beatrice Kennedy
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University
- Hugo Fitipaldi
- Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University
- Ulf Hammar
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University
- Marlena Maziarz
- Diabetic Complications Unit, Department of Clinical Sciences in Malmö, Lund University Diabetes Centre
- Neli Tsereteli
- Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University
- Nikolay Oskolkov
- Department of Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Lund University
- Georgios Varotsis
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University
- Camilla A. Franks
- Diabetic Complications Unit, Department of Clinical Sciences in Malmö, Lund University Diabetes Centre
- Diem Nguyen
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University
- Lampros Spiliopoulos
- Diabetic Complications Unit, Department of Clinical Sciences in Malmö, Lund University Diabetes Centre
- Hans-Olov Adami
- Clinical Effectiveness Group, Institute of Health and Society, University of Oslo
- Jonas Björk
- Division of Occupational and Environmental Medicine, Lund University
- Stefan Engblom
- Division of Scientific Computing, Department of Information Technology, Uppsala University
- Katja Fall
- Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University
- Anna Grimby-Ekman
- Biostatistics, School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg
- Jan-Eric Litton
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet
- Mats Martinell
- Department of Public Health and Caring Sciences, Uppsala University
- Anna Oudin
- Division of Occupational and Environmental Medicine, Lund University
- Torbjörn Sjöström
- Novus Group International AB
- Toomas Timpka
- Department of Health, Medicine and Caring Sciences, Linköping University
- Carole H. Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, University College London
- Mark S. Graham
- School of Biomedical Engineering and Imaging Sciences, King’s College London
- Julien Lavigne du Cadet
- ZOE Limited
- Andrew T. Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School
- Richard Davies
- ZOE Limited
- Sajaysurya Ganesh
- ZOE Limited
- Anna May
- ZOE Limited
- Sébastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King’s College London
- Joan Capdevila Pujol
- ZOE Limited
- Somesh Selvachandran
- ZOE Limited
- Jonathan Wolf
- ZOE Limited
- Tim D. Spector
- Department of Twin Research and Genetic Epidemiology, King’s College London
- Claire J. Steves
- Department of Twin Research and Genetic Epidemiology, King’s College London
- Maria F. Gomez
- Diabetic Complications Unit, Department of Clinical Sciences in Malmö, Lund University Diabetes Centre
- Paul W. Franks
- Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University
- Tove Fall
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University
- DOI
- https://doi.org/10.1038/s41467-022-29608-7
- Journal volume & issue
-
Vol. 13,
no. 1
pp. 1 – 12
Abstract
The app-based COVID Symptom Study was launched in Sweden in April 2020 to contribute to real-time COVID-19 surveillance using daily symptom reports from study participants. Here, the authors show how syndromic surveillance can be used to estimate regional COVID-19 prevalence and to predict later COVID-19 hospital admissions.
