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Record W4308668146 · doi:10.15585/mmwr.mm7145a2

Interim Recommendations from the Advisory Committee on Immunization Practices for the Use of Bivalent Booster Doses of COVID-19 Vaccines — United States, October 2022

2022· article· en· W4308668146 on OpenAlexfundno aff
Hannah G. Rosenblum, Megan J. Wallace, Monica Godfrey, Lauren E. Roper, Elisha Hall, Katherine E. Fleming-Dutra, Ruth Link‐Gelles, Tamara Pilishvili, Jennifer Williams, Danielle Moulia, Oliver Brooks, H. Keipp Talbot, Grace M. Lee, Beth P. Bell, Matthew F. Daley, Sarah Meyer, Sara E. Oliver, Evelyn Twentyman

Bibliographic record

VenueMMWR Morbidity and Mortality Weekly Report · 2022
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsnot available
FundersWake Forest School of MedicineResearch Institute, Nationwide Children's HospitalUniversity of California, Los AngelesBiomedical Advanced Research and Development AuthorityCollege of Medicine, Drexel UniversityCenters for Disease Control and PreventionPublic Health AgencyNorthwell HealthMarshfield Clinic Research InstituteAmerican Pharmacists AssociationDrexel UniversityNationwide Children's HospitalU.S. Department of DefenseMinnesota Department of HealthGeorge Washington UniversityStrongEmory UniversityBrown UniversityCouncil of State and Territorial EpidemiologistsPublic Health Agency of CanadaNational Institutes of HealthU.S. Department of Health and Human Services
KeywordsBivalent (engine)MedicineBooster doseBooster (rocketry)InterimVaccinationCoronavirus disease 2019 (COVID-19)VirologyAdvisory committeeFamily medicineTiterVirusInternal medicineLawManagement

Abstract

fetched live from OpenAlex

Four COVID-19 vaccines are currently approved for primary series vaccination in the United States under a Biologics License Application or authorized under an emergency use authorization (EUA) by the Food and Drug Administration (FDA), and recommended for primary series vaccination by the Advisory Committee on Immunization Practices (ACIP): 1) the 2- or 3-dose monovalent mRNA BNT162b2 (Pfizer-BioNTech, Comirnaty) COVID-19 vaccine; 2) the 2- or 3-dose monovalent mRNA mRNA-1273 (Moderna, Spikevax) COVID-19 vaccine; 3) the single-dose adenovirus vector-based Ad26.COV.S (Janssen [Johnson & Johnson]) COVID-19 vaccine; and 4) the 2-dose adjuvanted, protein subunit-based NVX-CoV2373 (Novavax) COVID-19 vaccine. The number of doses recommended is based on recipient age and immunocompromise status (1). For additional protection, FDA has amended EUAs to allow for COVID-19 booster doses in eligible persons (1). Because COVID-19 vaccines have demonstrated decreased effectiveness during the period when the Omicron variant (B.1.1.529) of SARS-CoV-2 predominated, bivalent booster doses (i.e., vaccine with equal components from the ancestral and Omicron strains) were considered for the express purpose of improving protection conferred by COVID-19 vaccine booster doses (2). During September-October 2022, FDA authorized bivalent mRNA vaccines for use as a booster dose in persons aged ≥5 years who completed any FDA-approved or FDA-authorized primary series and removed EUAs for monovalent COVID-19 booster doses (1). Pfizer-BioNTech and Moderna bivalent booster vaccines each contain equal amounts of spike mRNA from the ancestral and Omicron BA.4/BA.5 strains. After the EUA amendments, ACIP and CDC recommended that all persons aged ≥5 years receive 1 bivalent mRNA booster dose ≥2 months after completion of any FDA-approved or FDA-authorized monovalent primary series or monovalent booster doses.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.090
Threshold uncertainty score0.300

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.017
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0040.002
Research integrity0.0160.008
Insufficient payload (model declined to judge)0.0900.077

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.

Opus teacher head0.260
GPT teacher head0.432
Teacher spread0.172 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations161
Published2022
Admission routes1
Has abstractyes

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