Evidence map›Paper›PMID 40965885›Full record

ArticleJAMA network open2025

Scenario Projections of COVID-19 Burden in the US, 2024-2025.

Sara L Loo, Sung-Mok Jung, Lucie Contamin, Emily Howerton, Samantha J Bents, Harry Hochheiser, Michael C Runge, Claire P Smith, Erica C Carcelén, Katie Yan and 34 more

Abstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

44 authors.

Sara L LooJohns Hopkins University, Baltimore, Maryland.
Sung-Mok JungUniversity of North Carolina at Chapel Hill, Chapel Hill.
Lucie ContaminUniversity of Pittsburgh, Pittsburgh, Pennsylvania.
Emily HowertonPrinceton University, Princeton, New Jersey.
Samantha J BentsNational Institutes of Health Fogarty International Center, Bethesda, Maryland.
Harry HochheiserUniversity of Pittsburgh, Pittsburgh, Pennsylvania.
Michael C RungeUS Geological Survey, Laurel, Maryland.
Claire P SmithUniversity of North Carolina at Chapel Hill, Chapel Hill.
Erica C CarcelénJohns Hopkins University, Baltimore, Maryland.
Katie YanPenn State University, University Park, Pennsylvania.
Joseph C LemaitreUniversity of North Carolina at Chapel Hill, Chapel Hill.
Emily PrzykuckiUniversity of North Carolina at Chapel Hill, Chapel Hill.
Clifton D McKeeJohns Hopkins University, Baltimore, Maryland.
Koji SatoJohns Hopkins University, Baltimore, Maryland.
Allison L HillJohns Hopkins University, Baltimore, Maryland.
Matteo ChinazziNortheastern University, Boston, Massachusetts.
Jessica T DavisNortheastern University, Boston, Massachusetts.
Clara BayNortheastern University, Boston, Massachusetts.
Alessandro VespignaniNortheastern University, Boston, Massachusetts.
Shi ChenUniversity of North Carolina at Charlotte, Charlotte.
Rajib PaulUniversity of North Carolina at Charlotte, Charlotte.
Daniel JaniesUniversity of North Carolina at Charlotte, Charlotte.
Jean-Claude ThillUniversity of North Carolina at Charlotte, Charlotte.
Sean M MooreUniversity of Notre Dame, Notre Dame, Indiana.
T Alex PerkinsUniversity of Notre Dame, Notre Dame, Indiana.
Ajitesh SrivastavaUniversity of Southern California, Los Angeles.
Majd Al AawarUniversity of Southern California, Los Angeles.
Kaiming BiSchool of Public Health, The University of Texas Health Science Center at Houston, Houston.
Shraddha Ramdas BandekarUniversity of Texas at Austin, Austin.
Anass BouchnitaUniversity of Texas at El Paso, El Paso.
Spencer J FoxUniversity of Georgia, Athens, Georgia.
Lauren Ancel MeyersUniversity of Texas at Austin, Austin.
Przemyslaw PorebskiUniversity of Virginia, Charlottesville.
Srinivasan VenkatramananUniversity of Virginia, Charlottesville.
Bryan LewisUniversity of Virginia, Charlottesville.
Jiangzhuo ChenUniversity of Virginia, Charlottesville.
Madhav MaratheUniversity of Virginia, Charlottesville.
Michal Ben-NunPredictive Science Inc, San Diego, California.
James TurtlePredictive Science Inc, San Diego, California.
Pete RileyPredictive Science Inc, San Diego, California.
Katriona SheaPenn State University, University Park, Pennsylvania.
Cécile ViboudNational Institutes of Health Fogarty International Center, Bethesda, Maryland.
Justin LesslerUniversity of North Carolina at Chapel Hill, Chapel Hill.
Shaun TrueloveJohns Hopkins University, Baltimore, Maryland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: COVID-19 remains a disease with high burden in the US, prompting continued debate about optimal targets for annual vaccination. Objective: To project COVID-19 burden in the US for April 2024 to April 2025 under 6 scenarios of immune escape (20% and 50% per year) and levels of vaccine recommendation (no recommendation, vaccination for individuals at high risk only, vaccination for all eligible groups) and to assess the potential benefit of vaccine recommendations in reducing disease burden. Design, Setting, and Participants: For this decision analytical model, the US Scenario Modeling Hub, a collaborative modeling effort, convened 9 teams to provide scenario projections of US COVID-19 hospitalizations and deaths for April 2024 to April 2025, under 6 scenarios combining levels of immune escape and possible vaccine recommendations. Exposure: Annually reformulated vaccines were assumed to be 75% effective against hospitalization for variants circulating on June 15, 2024, and available on September 1, 2024. Age- and state-specific coverage was assumed to be as reported in September 2023 to April 2024. Main Outcomes and Measures: Ensemble estimates were made for weekly COVID-19 hospitalizations and deaths. Projections are presented for relative and absolute prevented hospitalizations and deaths averted due to vaccination over the April 2024 to April 2025 period. Results: For the US population (332 million, with an estimated 58 million aged ≥65 years), COVID-19 was expected to cause 814 000 (95% projection interval [PI], 400 000-1.2 million) hospitalizations and 54 000 (95% PI, 17 000-98 000) deaths for April 2024 to April 2025, comparable in magnitude to the prior year. Vaccination of high-risk groups only was projected to reduce hospitalizations (compared to no vaccination recommendation) by 76 000 (95% CI, 34 000-118 000) and deaths by 7000 (95% CI, 3000-11 000) across both immune escape scenarios. Compared with vaccinating high-risk groups only, a universal vaccine recommendation was projected to provide direct and indirect benefits, further preventing 11 000 hospitalizations and 1000 deaths in those aged 65 years and older. Conclusions and Relevance: In this decision analytical modeling study of COVID-19 burden in the US in 2024 to 2025, ensemble projections suggested that although vaccinating high-risk groups had substantial benefits in reducing disease burden, maintaining the vaccine recommendation for all individuals had the potential to save thousands more lives. Despite divergence of projections from observed disease trends in 2024 to 2025-possibly driven by variant emergence patterns and immune escape-averted COVID-19 burden due to vaccination was robust across immune escape scenarios, emphasizing the substantial benefit of broader vaccine availability for all individuals.

Indexed as

COVID-19COVID-19 VaccinesAdolescentAdultAgedAged, 80 and overChildChild, PreschoolCost of IllnessFemaleForecastingHospitalizationHumansInfantMaleMiddle AgedCOVID-19 Vaccines

Identifiers

PMID40965885
PMCPMC12447233

What OpenQuestion holds

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Registered trials

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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.