Evidence map›Paper›PMID 35313593›Full record

ArticlemedRxiv : the preprint server for health sciences2022

Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: a multi-model study.

Rebecca K Borchering, Luke C Mullany, Emily Howerton, Matteo Chinazzi, Claire P Smith, Michelle Qin, Nicholas G Reich, Lucie Contamin, John Levander, Jessica Kerr and 52 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 23 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

62 authors at 20 institutions in 5 countries.

Rebecca K BorcheringThe Pennsylvania State University (PSU).
Luke C MullanyJohns Hopkins University Applied Physics Lab (JHU/APL).
Emily HowertonPSU.
Matteo ChinazziNortheastern University (NEU).
Claire P SmithJohns Hopkins University Infectious Disease Dynamics (JHU-IDD).
Michelle QinHarvard University.
Nicholas G ReichUniversity of Massachusetts Amherst.
Lucie ContaminUniversity of Pittsburgh.
John LevanderUniversity of Pittsburgh.
Jessica KerrUniversity of Pittsburgh.
J EspinoUniversity of Pittsburgh.
Harry HochheiserUniversity of Pittsburgh.
Kaitlin LovettJHU/APL.
Matt KinseyJHU/APL.
Kate TallaksenJHU/APL.
Shelby WilsonJHU/APL.
Lauren ShinJHU/APL.
Joseph C LemaitreÉcole polytechnique fédérale de Lausanne.
Juan Dent HulseJHU-IDD.
Joshua KaminskyJHU-IDD.
Elizabeth C LeeJHU-IDD.
Jessica T DavisNEU.
Kunpeng MuNEU.
Xinyue XiongNEU.
Ana Pastore Y PionttiNEU.
Alessandro VespignaniNEU.
Ajitesh SrivastavaUniversity of Southern California.
Przemyslaw PorebskiUniversity of Virginia (UVA).
Srini VenkatramananUVA.
Aniruddha AdigaUVA.
Bryan LewisUVA.
Brian KlahnUVA.
Joseph OuttenUVA.
Benjamin HurtUVA.
Jiangzhuo ChenUVA.
Henning MortveitUVA.
Amanda WilsonUVA.
Madhav MaratheUVA.
Stefan HoopsUVA.
Parantapa BhattacharyaUVA.
Dustin MachiUVA.
Shi ChenUniversity of North Carolina at Charlotte (UNCC).
Rajib PaulUNCC.
Daniel JaniesUNCC.
Jean-Claude ThillUNCC.
Marta GalantiColumbia University (CU).
Teresa YamanaCU.
Sen PeiCU.
Jeffrey ShamanCU.
Guido EspanaUniversity of Notre Dame (UND).
Sean CavanyUND.
Sean MooreUND.
Alex PerkinsUND.
Jessica M HealyCenters for Disease Control and Prevention (CDC).
Rachel B SlaytonCDC.
Michael A JohanssonCDC.
Matthew BiggerstaffCDC.
Katriona SheaPSU.
Shaun A TrueloveJHU-IDD.
Michael C RungeU.S. Geological Survey.
Cécile ViboudNational Institutes of Health Fogarty International Center.
Justin LesslerUniversity of North Carolina.
University Vascular Associates · USUniversity of Pittsburgh · USHyattsville Community Development Corporation · USUluslararası Nakliyeciler Derneği · TRPacific States University · USCenter for Disease Dynamics, Economics & Policy · USCenters for Disease Control and Prevention · KEColumbia University · USÉcole Polytechnique Fédérale de Lausanne · CHHarvard University Press · USJohns Hopkins University Applied Physics Laboratory · USNational Institutes of Health · USPennsylvania State University · USUnited States Geological Survey · USUniversidad del Noreste · MXUniversity of Massachusetts Amherst · USUniversity of North Carolina at Charlotte · USUniversity of Notre Dame · USUniversity of Southern California · USUrology of Virginia · US

Funding

Research Services CoreP2CHD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN B GUZZO · 2015 to 2026
$9.6M
MIDAS Coordination CenterU24GM132013 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HOCHHEISER, HARRY S · 2019 to 2023
$8.1M
Statistical methods for real-time forecasts of infectious disease: expanding dynamic time-series and machine learning approaches for pandemic scenariosR35GM119582 · NIGMS · UNIVERSITY OF MASSACHUSETTS AMHERST · PI Nicholas G Reich · 2016 to 2026
$4.8M
Systems Analysis of Social Pathways of Epidemics to Reduce Health DisparitiesR01GM109718 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI MARATHE, ACHLA, VULLIKANTI, ANIL · 2014 to 2022
$3.6M
Quantifying Error Growth to Improve Infectious Disease Forecast AccuracyR01AI163023 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI JEFFREY L SHAMAN · 2021 to 2026
$3.3M
Merging machine learning and mechanistic models to improve prediction and inference in emerging epidemicsR01GM140564 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI EDWARDS, JESSIE, LESSLER, JUSTIN · 2021 to 2024
$1.8M
Assessing the impact of COVID-19 interventions on human mobility and SARS-CoV-2 transmission dynamics in the United StatesR21AI164391 · NIAID · UNIVERSITY OF NOTRE DAME · PI MOORE, SEAN MICHAEL · 2021 to 2022
$430k
NCEZID CDC HHS U01 CK000589NCIRD CDC HHS U01 IP001122NCIRD CDC HHS U01 IP001137NIAID NIH HHS R01 AI163023NIAID NIH HHS R21 AI164391NICHD NIH HHS P2C HD050924NIGMS NIH HHS R01 GM109718NIGMS NIH HHS R01 GM140564NIGMS NIH HHS R35 GM119582NIGMS NIH HHS U24 GM132013
6 · The paper itself

Abstract

Background: SARS-CoV-2 vaccination of persons aged 12 years and older has reduced disease burden in the United States. The COVID-19 Scenario Modeling Hub convened multiple modeling teams in September 2021 to project the impact of expanding vaccine administration to children 5-11 years old on anticipated COVID-19 burden and resilience against variant strains. Methods: Nine modeling teams contributed state- and national-level projections for weekly counts of cases, hospitalizations, and deaths in the United States for the period September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of: 1) presence vs. absence of vaccination of children ages 5-11 years starting on November 1, 2021; and 2) continued dominance of the Delta variant vs. emergence of a hypothetical more transmissible variant on November 15, 2021. Individual team projections were combined using linear pooling. The effect of childhood vaccination on overall and age-specific outcomes was estimated by meta-analysis approaches. Findings: Absent a new variant, COVID-19 cases, hospitalizations, and deaths among all ages were projected to decrease nationally through mid-March 2022. Under a set of specific assumptions, models projected that vaccination of children 5-11 years old was associated with reductions in all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios where children were not vaccinated. This projected effect of vaccinating children 5-11 years old increased in the presence of a more transmissible variant, assuming no change in vaccine effectiveness by variant. Larger relative reductions in cumulative cases, hospitalizations, and deaths were observed for children than for the entire U.S. population. Substantial state-level variation was projected in epidemic trajectories, vaccine benefits, and variant impacts. Conclusions: Results from this multi-model aggregation study suggest that, under a specific set of scenario assumptions, expanding vaccination to children 5-11 years old would provide measurable direct benefits to this age group and indirect benefits to the all-age U.S. population, including resilience to more transmissible variants.

Identifiers

PMID35313593
PMCPMC8936106
OpenAlexW4221129584

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.