MU Bhuiyan
Epidemiology of COVID-19 infection in young children under five years: A systematic review and meta-analysis
Bhuiyan, MU; Stiboy, Eunice; Hassan, MZ; Chan, Mei; Islam, MS; Haider, Najmul; Jaffe, Adam; Homaira, Nusrat
Authors
Eunice Stiboy
MZ Hassan
Mei Chan
MS Islam
Najmul Haider n.haider@keele.ac.uk
Adam Jaffe
Nusrat Homaira
Abstract
Introduction
Emerging evidence suggests young children are at greater risk of COVID-19 infection than initially predicted. However, a comprehensive understanding of epidemiology of COVID-19 infection in young children under five years, the most at-risk age-group for respiratory infections, remain unclear. We conducted a systematic review and meta-analysis of epidemiological and clinical characteristics of COVID-19 infection in children under five years.
Method
Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses , we searched several electronic databases (Pubmed, EMBASE, Web of Science, and Scopus) with no language restriction for published epidemiological studies and case-reports reporting laboratory-confirmed COVID-19 infection in children under five years until June 4, 2020. We assessed pooled prevalence for key demographics and clinical characteristics using Freeman-Tukey double arcsine random-effects model for studies except case-reports. We evaluated risk of bias separately for case-reports and other studies.
Results
We identified 1,964 articles, of which, 65 articles were eligible for systematic review that represented 1,214 children younger than five years with laboratory-confirmed COVID-19 infection. The pooled estimates showed that 50% young COVID-19 cases were infants (95% CI: 36% - 63%, 27 studies); 53% were male (95% CI: 41% - 65%, 24 studies); 43% were asymptomatic (95% CI: 15% - 73%, 9 studies) and 7% (95% CI: 0% - 30%, 5 studies) had severe disease that required intensive-care-unit admission. Of 139 newborns from COVID-19 infected mothers, five (3.6%) were COVID-19 positive. There was only one death recorded.
Discussion
This systematic review reports the largest number of children younger than five years with COVID-19 infection till date. Our meta-analysis shows nearly half of young COVID-19 cases were asymptomatic and half were infants, highlighting the need for ongoing surveillance to better understand the epidemiology, clinical pattern, and transmission of COVID-19 to develop effective preventive strategies against COVID-19 disease in young paediatric population.
Citation
Bhuiyan, M., Stiboy, E., Hassan, M., Chan, M., Islam, M., Haider, N., …Homaira, N. (2021). Epidemiology of COVID-19 infection in young children under five years: A systematic review and meta-analysis. Vaccine, 39(4), 667 - 677. https://doi.org/10.1016/j.vaccine.2020.11.078
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 30, 2020 |
Online Publication Date | Dec 5, 2020 |
Publication Date | 2021-01 |
Publicly Available Date | May 30, 2023 |
Journal | Vaccine |
Print ISSN | 0264-410X |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 39 |
Issue | 4 |
Pages | 667 - 677 |
DOI | https://doi.org/10.1016/j.vaccine.2020.11.078 |
Publisher URL | https://www.sciencedirect.com/science/article/pii/S0264410X2031570X?via%3Dihub |
Files
2. 26. 2021. 1 Bhuiyan et al_Epidemiology-of-COVID-19-infection-in-young-children-under-five-ye_2021_Vacc.pdf
(2.1 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by-nc/4.0/
You might also like
Occurrence of tuberculosis among people exposed to cattle in Bangladesh
(2023)
Journal Article
Human Exposure to Bats, Rodents and Monkeys in Bangladesh
(2023)
Journal Article
Downloadable Citations
About Keele Repository
Administrator e-mail: research.openaccess@keele.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search