Coronavirus Disease 2019 (COVID-19) in Children: Vulnerable or Spared? A Systematic Review
Bibliographic record
Abstract
The ongoing pandemic of coronavirus disease 2019 (COVID-19) has affected people from all cultures, religions, gender, and age groups around the world. In the last few months, several studies have been conducted on various aspects of COVID-19. Our goal was to see if the pediatric population is vulnerable to this infection. In this review, we conducted extensive research mainly by using the PubMed database. We used Medical Subject Headings (MeSH) and associated keywords to engage in an extensive search focussing on COVID-19 in the pediatric population. We discovered that most of the studies were from China, and some of them were in the Chinese language. However, English translations of many of the studies were available. For accessing the relevant statistical data, we relied on the World Health Organization (WHO) resources and the official website of the Ontario Government (ontario.ca). Most of the studies showed that the virus has affected the pediatric population. However, we found some differences among these studies regarding the severity of symptoms in children affected by COVID-19. While a few studies stated that the virus has presented with milder symptoms in the pediatric population, some studies have presented data of children who have suffered life-threatening complications due to COVID-19. Although the data is limited, we have been able to conclude from the studies we reviewed that COVID-19 does indeed affect children the same way as any other age group. Moreover, children can act as carriers of the virus and can endanger the lives of other individuals. Besides, neonates and infants can easily acquire the infection from family members without having any exposure to the outside world. Hence, utmost care should be taken while handling this population. More trials and studies should be conducted to analyze the impact of early diagnosis of infection in children and its management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".