COVID‐19 vaccination in children and university students
COVID‐19 vaccination in children and university students is a research paper published in European Journal of Clinical Investigation (2021). On theSindex it has a DataRank of 0.533. It has been cited 34 times.
Abstract
Strategies for the use of COVID-19 vaccines in children and young adults (in particular university students) are hotly debated and important to optimize. As of late August 2021, recommendations on the use of these vaccines in children vary across different countries. Recommendations are more uniform for vaccines in young adults, but vaccination uptake in this age group shows a large range across countries. Mandates for vaccination of university students are a particularly debated topic with many campuses endorsing mandates in the USA in contrast to European countries, at least as of August 2021. The commentary discusses the potential indirect impact of vaccination of youth on the COVID-19 burden of disease for other age groups and societal functioning at large, estimates of direct impact on reducing fatalities and nonlethal COVID-19-related events in youth, estimates of potential lethal and nonlethal adverse events from vaccines and differential considerations that may exist in the USA, European countries and nonhigh-income countries. Decision-making for deploying COVID-19 vaccines in young people is subject to residual uncertainty on the future course of the pandemic and potential evolution towards endemicity. Rational recommendations would also benefit from better understanding of the clinical and sociodemographic features of COVID-19 risk in young populations and from dissecting the role of re-infections and durability of natural vs. vaccine-induced immunity.
›Data sources & pipeline
FAIR Checklist
Context only (not used in score)- Has DOI
- Open Access
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
DataRank Breakdown
Base Score Contribution
0.533
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.