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Mason AE, Hecht FM, Davis SK, Natale JL, Hartogensis W, Damaso N, Claypool KT, Dilchert S, Dasgupta S, Purawat S, Viswanath VK, Klein A, Chowdhary A, Fisher SM, Anglo C, Puldon KY, Veasna D, Prather JG, Pandya LS, Fox LM, Busch M, Giordano C, Mercado BK, Song J, Jaimes R, Baum BS, Telfer BA, Philipson CW, Collins PP, Rao AA, Wang EJ, Bandi RH, Choe BJ, Epel ES, Epstein SK, Krasnoff JB, Lee MB, Lee SW, Lopez GM, Mehta A, Melville LD, Moon TS, Mujica-Parodi LR, Noel KM, Orosco MA, Rideout JM, Robishaw JD, Rodriguez RM, Shah KH, Siegal JH, Gupta A, Altintas I, Smarr BL. Detection of COVID-19 using multimodal data from a wearable device: results from the first TemPredict Study. Sci Rep 2022; 12:3463. [PMID: 35236896 PMCID: PMC8891385 DOI: 10.1038/s41598-022-07314-0] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 02/14/2022] [Indexed: 12/23/2022] Open
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.
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Affiliation(s)
- Ashley E Mason
- Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA.
| | - Frederick M Hecht
- Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA
| | - Shakti K Davis
- MIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA
| | - Joseph L Natale
- Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA
| | - Wendy Hartogensis
- Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA
| | - Natalie Damaso
- MIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA
| | - Kajal T Claypool
- MIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Stephan Dilchert
- Department of Management, Zicklin School of Business, Baruch College, The City University of New York, New York, NY, USA
| | - Subhasis Dasgupta
- San Diego Supercomputer Center, University of California San Diego, San Diego, CA, USA
| | - Shweta Purawat
- San Diego Supercomputer Center, University of California San Diego, San Diego, CA, USA
| | - Varun K Viswanath
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Amit Klein
- Department of Bioengineering: Bioinformatics, University of California San Diego, San Diego, CA, USA
| | - Anoushka Chowdhary
- Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA
| | - Sarah M Fisher
- Department of Psychology, Drexel University, Pennsylvania, PA, USA
| | - Claudine Anglo
- Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA
| | - Karena Y Puldon
- Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA
| | - Danou Veasna
- Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA
| | - Jenifer G Prather
- Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA
| | - Leena S Pandya
- Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA
| | - Lindsey M Fox
- Osher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA
| | - Michael Busch
- Vitalant Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Casey Giordano
- Department of Psychology, University of Minnesota - Twin Cities, Minneapolis, MN, USA
| | | | - Jining Song
- San Diego Supercomputer Center, University of California San Diego, San Diego, CA, USA
| | - Rafael Jaimes
- MIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA
| | - Brian S Baum
- MIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA
| | - Brian A Telfer
- MIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA
| | - Casandra W Philipson
- MIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA
| | - Paula P Collins
- MIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA
| | - Adam A Rao
- School of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Edward J Wang
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Rachel H Bandi
- Department of Anesthesiology, Northwestern McGaw Medical Center, Feinberg School of Medicine, Chicago, IL, USA
| | - Bianca J Choe
- Department of Emergency Medicine, University of California Los Angeles Health, Los Angeles, CA, USA
| | - Elissa S Epel
- Center for Health and Community, University of California San Francisco, San Francisco, CA, USA
| | - Stephen K Epstein
- Department of Emergency Medicine, Beth Israel Deaconess Medical Center Boston, Boston, MA, USA
| | - Joanne B Krasnoff
- Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, USA
| | - Marco B Lee
- Department of Neurosurgery, Santa Clara Valley Medical Center, Stanford University, San Jose, CA, USA
| | - Shi-Wen Lee
- Department of Emergency Medicine, Jamaica Hospital Medical Center, Jamaica, NY, USA
| | - Gina M Lopez
- Department of Emergency Medicine, Boston Medical Center, Boston, MA, USA
| | - Arpan Mehta
- Department of Anesthesiology: Pain Management and Perioperative Medicine, University of Miami, Miami, FL, USA
| | - Laura D Melville
- Department of Emergency Medicine, New York Presbyterian Brooklyn Methodist Hospital, Brooklyn, NY, USA
| | - Tiffany S Moon
- Department of Anesthesiology and Pain Management, University of Texas Southwestern, Dallas, TX, USA
| | - Lilianne R Mujica-Parodi
- Department of Biomedical Engineering, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Kimberly M Noel
- Stony Brook Medicine, Stony Brook University Renaissance School of Medicine, Stony Brook, NY, USA
| | - Michael A Orosco
- Department of Anesthesia: Perioperative and Pain Medicine, Kaiser Permanente San Diego, San Diego, CA, USA
| | - Jesse M Rideout
- Department of Emergency Medicine, Tufts Medical Center, Boston, MA, USA
| | - Janet D Robishaw
- Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, USA
| | - Robert M Rodriguez
- Department of Emergency Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Kaushal H Shah
- Weill Cornell Medical Center, Weill Cornell Medical School, New York, NY, USA
| | - Jonathan H Siegal
- New York Presbyterian Queens, Weill-Cornell Medical College, Queens, NY, USA
| | - Amarnath Gupta
- Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA
- San Diego Supercomputer Center, University of California San Diego, San Diego, CA, USA
| | - Ilkay Altintas
- Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA
- San Diego Supercomputer Center, University of California San Diego, San Diego, CA, USA
| | - Benjamin L Smarr
- Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA
- Department of Bioengineering: Bioinformatics, University of California San Diego, San Diego, CA, USA
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