Global Prevalence of Post-Coronavirus Disease 2019 (COVID-19) Condition or Long COVID: A Meta-Analysis and Systematic Review

  1. Chen Chen
  2. Spencer R Haupert
  3. Lauren Zimmermann
  4. Xu Shi
  5. Lars G Fritsche
  6. Bhramar Mukherjee

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

This study aims to examine the worldwide prevalence of post-coronavirus disease 2019 (COVID-19) condition, through a systematic review and meta-analysis.

Methods

PubMed, Embase, and iSearch were searched on July 5, 2021 with verification extending to March 13, 2022. Using a random-effects framework with DerSimonian-Laird estimator, we meta-analyzed post-COVID-19 condition prevalence at 28+ days from infection.

Results

Fifty studies were included, and 41 were meta-analyzed. Global estimated pooled prevalence of post-COVID-19 condition was 0.43 (95% confidence interval [CI], .39–.46). Hospitalized and nonhospitalized patients had estimates of 0.54 (95% CI, .44–.63) and 0.34 (95% CI, .25–.46), respectively. Regional prevalence estimates were Asia (0.51; 95% CI, .37–.65), Europe (0.44; 95% CI, .32–.56), and United States of America (0.31; 95% CI, .21–.43). Global prevalence for 30, 60, 90, and 120 days after infection were estimated to be 0.37 (95% CI, .26–.49), 0.25 (95% CI, .15–.38), 0.32 (95% CI, .14–.57), and 0.49 (95% CI, .40–.59), respectively. Fatigue was the most common symptom reported with a prevalence of 0.23 (95% CI, .17–.30), followed by memory problems (0.14; 95% CI, .10–.19).

Conclusions

This study finds post-COVID-19 condition prevalence is substantial; the health effects of COVID-19 seem to be prolonged and can exert stress on the healthcare system.

Article activity feed

  1. Version published to 10.1093/infdis/jiac136
  2. ScreenIT

    SciScore for 10.1101/2021.11.15.21266377: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    BlindingScreeners 1 and 2 performed both phases of the screening independently (i.e., were blinded).
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    22 The literature databases, PubMed and Embase for published articles, as well as iSearch for preprint articles from bioRxiv, medRxiv, SSRN, Research Square, and preprints.org, were searched on July 5, 2021, and search verification was extended through August 12, 2021.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Embase
    suggested: (EMBASE, RRID:SCR_001650)
    bioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)
    We defined PASC as having any symptoms, or at least one new or persisting symptom during the follow-up time.
    PASC
    suggested: (PASC , RRID:SCR_016642)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    This leads to the several limitations of this systematic review and meta- analysis.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a protocol registration statement.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.11.15.21266377v1 on medRxiv