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Feasibility of using intermittent active monitoring of vital signs by smartphone users to predict SARS-CoV-2 PCR positivity.

Published version
Peer-reviewed

Repository DOI


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Authors

Dolezalova, Nikola 
Gkrania-Klotsas, Effrossyni 
Morelli, Davide 
Moore, Alex 
Cunningham, Adam C 

Abstract

Early detection of highly infectious respiratory diseases, such as COVID-19, can help curb their transmission. Consequently, there is demand for easy-to-use population-based screening tools, such as mobile health applications. Here, we describe a proof-of-concept development of a machine learning classifier for the prediction of a symptomatic respiratory disease, such as COVID-19, using smartphone-collected vital sign measurements. The Fenland App study followed 2199 UK participants that provided measurements of blood oxygen saturation, body temperature, and resting heart rate. Total of 77 positive and 6339 negative SARS-CoV-2 PCR tests were recorded. An optimal classifier to identify these positive cases was selected using an automated hyperparameter optimisation. The optimised model achieved an ROC AUC of 0.695 ± 0.045. The data collection window for determining each participant's vital sign baseline was increased from 4 to 8 or 12 weeks with no significant difference in model performance (F(2) = 0.80, p = 0.472). We demonstrate that 4 weeks of intermittently collected vital sign measurements could be used to predict SARS-CoV-2 PCR positivity, with applicability to other diseases causing similar vital sign changes. This is the first example of an accessible, smartphone-based remote monitoring tool deployable in a public health setting to screen for potential infections.

Description

Acknowledgements: We would like to thank all the participants who kindly took part in the study.


Funder: Huma Therapeutics ltd, United Kingdom


Funder: National Institute of Health Research


Funder: Biomedical Research Centre in Cambridge

Keywords

Humans, SARS-CoV-2, Smartphone, Feasibility Studies, COVID-19, Polymerase Chain Reaction, Body Temperature, COVID-19 Testing

Journal Title

Sci Rep

Conference Name

Journal ISSN

2045-2322
2045-2322

Volume Title

13

Publisher

Springer Science and Business Media LLC
Sponsorship
MRC (MC_UU_00006/1)
Cambridge University Hospitals NHS Foundation Trust (CUH) (146281)
National Institute for Health and Care Research (IS-BRC-1215-20014)