Evidence map›Paper›PMID 41654404›Full record

ArticleThe Lancet. Digital health2026

Smartwatch-derived versus self-reported outcomes of physiological recovery after COVID-19, influenza, and group A streptococcus: a 2-year prospective cohort study.

Yosi Levi, Varun Gande, Erez Shmueli, Tal Patalon, Sivan Gazit, Margaret L Brandeau, Dan Yamin

Erratum issuedAbstract read
In one paragraph

Article in The Lancet. Digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Yosi LeviSchool of Industrial and Intelligent Systems Engineering, Tel Aviv University, Tel Aviv, Israel.
Varun GandeDepartment of Management Science and Engineering, Stanford University, Stanford, CA, USA.
Erez ShmueliSchool of Industrial and Intelligent Systems Engineering, Tel Aviv University, Tel Aviv, Israel.
Tal PatalonKahn Sagol Maccabi Research and Innovation Center, Maccabi Healthcare Services, Tel Aviv, Israel.
Sivan GazitKahn Sagol Maccabi Research and Innovation Center, Maccabi Healthcare Services, Tel Aviv, Israel.
Margaret L BrandeauDepartment of Management Science and Engineering, Stanford University, Stanford, CA, USA.
Dan YaminSchool of Industrial and Intelligent Systems Engineering, Tel Aviv University, Tel Aviv, Israel; Department of Management Science and Engineering, Stanford University, Stanford, CA, USA. Electronic address: yamind@tauex.tau.ac.il.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate detection of recovery from communicable diseases enables timely care and helps prevent complications and chronic conditions. We aimed to investigate the time for self-reported symptom recovery and digital recovery based on physiological data from smartwatches after infection with COVID-19, influenza, and group A streptococcus (GAS), and how activity levels changed throughout recovery.

methodsWe analysed data on COVID-19, influenza, and GAS from a 2-year prospective cohort study in Israel, incorporating smartwatch data, self-reported symptoms, and medical records. Eligible individuals were aged at least 18 years, Maccabi Healthcare Services members for at least 2 years, using their own smartphone, and could provide informed consent. Participants were recruited through social media and word-of-mouth. Controls were matched by age and sex, with post-hoc validation confirming similar baseline health profiles. At enrolment, participants completed a one-time questionnaire, received a smartwatch, and downloaded two applications to complete daily questionnaires and self-reports; passive data (eg, daily steps, distance walked, active time, active calories) and physiological measures (eg, heart rate and heart rate variability-based stress) were also collected from the smartwatches. Positive diagnoses for COVID-19, influenza, or GAS were identified from electronic medical records or self-reported through the app after home testing. The primary outcome measure was the duration of lag between self-reported symptom resolution and digital recovery, defined as the return of smartwatch-detected physiology (heart rate and heart rate variability-based stress during sedentary periods) to baseline levels. Digital recovery was assessed in all participants who tested positive for the disease, and valid smartwatch and questionnaire data were available. We examined this lag across illnesses and by severity (mild or moderate-to-severe). We also analysed behavioural and activity measures, such as daily steps, active calories, active time, and total distance, from smartwatch data to contextualise recovery trajectories.

findingsDuring the study period Nov 16, 2020, to May 11, 2023, involving 4795 participants, 3097 COVID-19 cases, 633 influenza cases, and 380 GAS cases occurred. 2742 participants had COVID-19 at least once during the 2-year follow up, for which 1421 (51·8%) were female and 1321 (48·2%) were male, with a median age of 44·0 years (IQR 33·0-56·0). Likewise, of 531 participants who had influenza at least once, 305 (57·4%) were female and 226 (42·6%) were male, with a median age of 51·0 years (IQR 38·0-61·0). For 334 participants who had GAS at least once, 191 (57·2%) were female and 143 (42·8%) were male, with a median age of 38·0 years (IQR 32·0-47·0). Digital recovery (measured by smartwatches) lagged substantially behind self-reported symptom resolution in most cases and both varied by illness severity and type: COVID-19 mild cases showed 8·53 days (95% CI 7·89 to 9·17) to self-reported symptom resolution, with an additional 7·14 days (6·49 to 7·78) to digital recovery, and moderate-to-severe cases showed 12·05 days (11·38 to 12·72) to symptom resolution with an additional 60·23 days (59·58 to 60·89) to digital recovery; influenza mild cases showed 7·98 days (6·66 to 9·29) to symptom resolution with an additional 2·51 days (1·21 to 3·81) to digital recovery, and moderate-to-severe cases showed 12·06 days (10·81 to 13·31) with an additional 7·85 days (6·62 to 9·08) to digital recovery; and GAS mild cases showed 7·95 days (6·45 to 9·45) to symptom resolution with an additional -1·12 days (-2·59 to 0·34) to digital recovery and moderate-to-severe cases showed 9·75 days (8·32 to 11·19) with an additional 4·37 days (2·97 to 5·76) to digital recovery. Markedly, when participants reported being symptom-free, their daily steps, distance walked, active time, and active calories returned to baseline levels, indicating a restoration of their regular daily routines.

interpretationPublic health recommendations suggest individuals can resume normal activities 5 days after symptom cessation. However, our study finds that full recovery can take longer, indicating that delayed return to normal activities might be warranted for those who had fever or other severe symptoms. Smartwatches can help identify patients who have not fully recovered from infection. Future research should determine whether identifying these people, and modifying their behaviour appropriately, leads to improved outcomes and can reduce the burden of communicable diseases.

fundingEuropean Research Council, the Israel Science Foundation within the Israel Precision Medicine Partnership programme, and a Koret Foundation gift for Smart Cities and Digital Living.

Indexed as

COVID-19Influenza, HumanSelf ReportStreptococcal InfectionsAdultAgedDigital HealthFemaleHumansIsraelMaleMiddle AgedPost-Acute COVID-19 SyndromeProspective StudiesSARS-CoV-2Smartphone

Identifiers

PMID41654404
PMCPMC12992200

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.