The toll of COVID-19 on African children: A descriptive analysis on COVID-19-related morbidity and mortality among the pediatric population in Sub-Saharan Africa

  1. Sabina Rodriguez Velásquez
  2. Léa Jacques
  3. Jyoti Dalal
  4. Paolo Sestito
  5. Zahra Habibi
  6. Akarsh Venkatasubramanian
  7. Benedict Nguimbis
  8. Sara Botero Mesa
  9. Cleophas Chimbetete
  10. Olivia Keiser
  11. Benido Impouma
  12. Franck Mboussou
  13. George Sie William
  14. Nsenga Ngoy
  15. Ambrose Talisuna
  16. Abdou Salam Gueye
  17. Cristina Barroso Hofer
  18. Joseph Waogodo Cabore

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Abstract

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  1. Version published to 10.1016/j.ijid.2021.07.060
  2. ScreenIT

    SciScore for 10.1101/2021.07.02.21259857: (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
    Microsoft Excel, the R software (version 4.0.2) and Python (version 3.7.7) were used to perform the data analyses.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    Python
    suggested: (IPython, RRID:SCR_001658)

    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:
    Strengths and limitations: To our knowledge, this is the largest analysis on individual-level pediatric COVID-19 cases in Sub-Saharan Africa. Data were presented at three levels: national, regional and in Sub-Saharan Africa as a whole. However, due to constraints on completeness and quality of available data, we could only include data of 15 countries. The cumulative incidence rates differed significantly between countries ranging from 0.2 in Chad to 94.2 in Eswatini. The large differences may partly be explained by differential underreporting of cases and different testing criteria between countries. Nguimkeu et al. (2021), noted that underreporting may be explained by an insufficient diagnostic capacity in certain regions in Sub-Saharan Africa (Nguimkeu and Tadadjeu, 2021). Available data from our focus countries also reflected only few deaths among children, if any. COVID-19 responses in Sub-Saharan Africa have benefited from dynamic, comprehensive, and timely efforts from governments, often in collaboration with various partners. Inferences for health policy and governance: The COVID-19 pandemic has highlighted gaps in data management in health systems across the world. Experiences from the pandemic have evidenced the need for effective, efficient, responsible, and participatory governance to ensure children’s health data is used responsibly and not misused (Ienca and Vayena, 2020). Inferences from this research strengthen recent advocacy calls on the urgent need for sex-...

    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 10.1101/2021.07.02.21259857 on medRxiv