Asymptomatic SARS-CoV-2 Infection by Age: A Global Systematic Review and Meta-analysis

  1. Bing Wang
  2. Prabha Andraweera
  3. Salenna Elliott
  4. Hassen Mohammed
  5. Zohra Lassi
  6. Ashley Twigger
  7. Chloe Borgas
  8. Shehani Gunasekera
  9. Shamez Ladhani
  10. Helen Siobhan Marshall

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Abstract

Asymptomatic SARS-CoV-2 infections have raised concerns for public health policies to manage epidemics. This systematic review and meta-analysis aimed to estimate the age-specific proportion of asymptomatic SARS-CoV-2 infected persons globally by year of age.

Methods:

We searched PubMed, Embase, medRxiv and Google Scholar on September 10, 2020, and March 1, 2021. We included studies conducted during January to December 2020, before routine vaccination against COVID-19. Because we expected the relationship between the asymptomatic proportion and age to be nonlinear, multilevel mixed-effects logistic regression (QR decomposition) with a restricted cubic spline was used to model asymptomatic proportions as a function of age.

Results:

A total of 38 studies were included in the meta-analysis. In total, 6556 of 14,850 cases were reported as asymptomatic. The overall estimate of the proportion of people who became infected with SARS-CoV-2 and remained asymptomatic throughout infection was 44.1% (6556/14,850, 95% CI: 43.3%–45.0%). The predicted asymptomatic proportion peaked in children (36.2%, 95% CI: 26.0%–46.5%) at 13.5 years, gradually decreased by age and was lowest at 90.5 years of age (8.1%, 95% CI: 3.4%–12.7%).

Conclusions:

Given the high rates of asymptomatic carriage in adolescents and young adults and their active role in virus transmission in the community, heightened vigilance and public health strategies are needed among these individuals to prevent disease transmission.

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  1. Version published to 10.1097/inf.0000000000003791
  2. ScreenIT

    SciScore for 10.1101/2022.05.05.22274697: (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.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The following study characteristics were considered when estimating the proportion of asymptomatic infections: study period, study population, country, SARS-CoV-2 infection definition, asymptomatic case definition and follow-up period. 2.2. Search Strategy: We searched PubMed, Embase, medRxiv and Google Scholar on 10 September 2020 and 1 March 2021 using keywords COVID-19, SARS-CoV-2, 2019-nCoV, coronavirus disease 2019 AND asymptomatic.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Embase
    suggested: (EMBASE, RRID:SCR_001650)
    Google Scholar
    suggested: (Google Scholar, RRID:SCR_008878)
    These search terms included combinations of Medical Subject Headings (MeSH)/Emtree and text words contained in the title and abstract. 2.3.
    MeSH)/Emtree
    suggested: None
    Eight authors (BW, PA, SE, HM, ZL, AT, CB, SG) used an online form in Covidence or a Microsoft Excel spreadsheet to extract the following information: study design, setting, study period, study population (sample size, mean or median age, case definition, etc.), country, follow-up duration, and outcomes (number of people sampled/tested, total number of SARS-CoV-2 positive persons, number of asymptomatic SARS-CoV-2 positive persons). 2.5.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.
    • No protocol registration statement was detected.

    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 10.1101/2022.05.05.22274697v1 on medRxiv