@article{86543f89b86b4304a96051ac6b200fb4,
title = "Detection of COVID-19 using multimodal data from a wearable device: results from the first TemPredict Study",
abstract = "Early detection of diseases such as COVID-19 could be a critical tool in reducing disease transmission by helping individuals recognize when they should self-isolate, seek testing, and obtain early medical intervention. Consumer wearable devices that continuously measure physiological metrics hold promise as tools for early illness detection. We gathered daily questionnaire data and physiological data using a consumer wearable (Oura Ring) from 63,153 participants, of whom 704 self-reported possible COVID-19 disease. We selected 73 of these 704 participants with reliable confirmation of COVID-19 by PCR testing and high-quality physiological data for algorithm training to identify onset of COVID-19 using machine learning classification. The algorithm identified COVID-19 an average of 2.75 days before participants sought diagnostic testing with a sensitivity of 82% and specificity of 63%. The receiving operating characteristic (ROC) area under the curve (AUC) was 0.819 (95% CI [0.809, 0.830]). Including continuous temperature yielded an AUC 4.9% higher than without this feature. For further validation, we obtained SARS CoV-2 antibody in a subset of participants and identified 10 additional participants who self-reported COVID-19 disease with antibody confirmation. The algorithm had an overall ROC AUC of 0.819 (95% CI [0.809, 0.830]), with a sensitivity of 90% and specificity of 80% in these additional participants. Finally, we observed substantial variation in accuracy based on age and biological sex. Findings highlight the importance of including temperature assessment, using continuous physiological features for alignment, and including diverse populations in algorithm development to optimize accuracy in COVID-19 detection from wearables.",
author = "Mason, {Ashley E.} and Hecht, {Frederick M.} and Davis, {Shakti K.} and Natale, {Joseph L.} and Wendy Hartogensis and Natalie Damaso and Claypool, {Kajal T.} and Stephan Dilchert and Subhasis Dasgupta and Shweta Purawat and Viswanath, {Varun K.} and Amit Klein and Anoushka Chowdhary and Fisher, {Sarah M.} and Claudine Anglo and Puldon, {Karena Y.} and Danou Veasna and Prather, {Jenifer G.} and Pandya, {Leena S.} and Fox, {Lindsey M.} and Michael Busch and Casey Giordano and Mercado, {Brittany K.} and Jining Song and Rafael Jaimes and Baum, {Brian S.} and Telfer, {Brian A.} and Philipson, {Casandra W.} and Collins, {Paula P.} and Rao, {Adam A.} and Wang, {Edward J.} and Bandi, {Rachel H.} and Choe, {Bianca J.} and Epel, {Elissa S.} and Epstein, {Stephen K.} and Krasnoff, {Joanne B.} and Lee, {Marco B.} and Lee, {Shi Wen} and Lopez, {Gina M.} and Arpan Mehta and Melville, {Laura D.} and Moon, {Tiffany S.} and Mujica-Parodi, {Lilianne R.} and Noel, {Kimberly M.} and Orosco, {Michael A.} and Rideout, {Jesse M.} and Robishaw, {Janet D.} and Rodriguez, {Robert M.} and Shah, {Kaushal H.} and Siegal, {Jonathan H.} and Amarnath Gupta and Ilkay Altintas and Smarr, {Benjamin L.}",
note = "Funding Information: The USAMRDC under the Department of Defense (DOD) provided financial support for this work. This effort was funded under MTEC solicitation MTEC-20-12-Diagnostics-023 and is funded by the USAMRDC under the Department of Defense. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the U.S. Government. The #StartSmall foundation provided financial support for this work. The US Department of Defense Air Force Office of Scientific Research, through the Massachusetts Institute of Technology Lincoln Laboratory (MIT-LL), provided financial support for this work. Oura Health Oy provided 1400 pieces of hardware and financial support in the form of a sponsored research contract. Publisher Copyright: {\textcopyright} 2022, The Author(s).",
year = "2022",
month = dec,
doi = "10.1038/s41598-022-07314-0",
language = "English (US)",
volume = "12",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
number = "1",
}