COVID-19 Infection in Children: Estimating Pediatric Morbidity and Mortality

  1. Michelle Barton
  2. Kayur Mehta
  3. Kriti Kumar
  4. Jielin Lu
  5. Nicole Le Saux
  6. Margaret Sampson
  7. Joan Robinson

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

BACKGROUND

Estimates of pediatric morbidity and mortality from COVID-19 are vital for planning optimal use of human and material resources throughout this pandemic.

METHODS

Government websites from countries with minimum 1000 cases in adults and children on April 13, 2020 were searched to find the number of cases confirmed in children, the age range, and the number leading to hospitalization, intensive care unit (ICU) admission or death. A systematic literature search was performed April 13, 2020 to find additional data from cases series.

RESULTS

Data on pediatric cases were available from government websites for 23 of the 70 countries with minimum 1000 cases by April 13, 2020. Of 424 978 cases in these 23 countries, 8113 (1.9%) occurred in children. Nine publications provided data from 4251 cases in 4 additional countries. Combining data from the websites and the publications, 330 of 2361 cases required admission (14%). The ICU admission rate was 2.2 % of confirmed cases (44 of 2031) and 7.2% of admitted children (23 of 318). Death was reported for 15 cases.

CONCLUSION

Children accounted for 1.9% of confirmed cases. The true incidence of pediatric infection and disease will only be known once testing is expanded to individuals with less severe or no symptoms. Admission rates vary from 0.3 to 10% of confirmed cases (presumably varying with the threshold for testing) with about 7% of admitted children requiring ICU care. Death is rare in middle and high income countries.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.05.05.20091751: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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:
    The main limitation of this study is that pediatric data are yet to be reported for most countries, data would not have been recently been updated on all websites, and data on hospitalizations were missing from most websites. Data from the publications will already be out of date. The number of reported cases is very much determined by testing algorithms which may favor testing of elderly adults over children. The age ranges that were analyzed were not uniform with the upper limit for the pediatric age range varying from 14 to 19 years. The data in the current study may under-estimate ICU admissions and deaths. Initial data from China in adults with pneumonia showed a lag of about 12 days between symptom onset and admission so these outcomes may yet occur for children in the current study.26 The impact of COVID-19 on children will undoubtedly differ in low-income countries; intensive care is often not available and the proportion of children in the population is much higher.27 In conclusion, children account for a small percentage of symptomatic COVID-19 infections and severe and critical cases are rare. Further studies are required to delineate the true spectrum of pediatric disease worldwide and, perhaps even more importantly, the potential for children to develop severe disease if reinfection with COVID-19 or a similar coronavirus occurs later in life.

    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.

    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.

  2. Version published to 10.1101/2020.05.05.20091751v1 on medRxiv