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Record W4220838548 · doi:10.1101/2022.03.17.22272555

Relative effectiveness of booster vs. 2-dose mRNA Covid-19 vaccination in the Veterans Health Administration: Self-controlled risk interval analysis

2022· preprint· en· W4220838548 on OpenAlexaff
Caroline Korves, Héctor S. Izurieta, Jeremy Smith, Gabrielle Zwain, Ethan I. Powell, Abirami Balajee, Kathy Ryder, Yinong Young‐Xu

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsIsland Health
FundersOffice of Rural HealthU.S. Food and Drug AdministrationPfizerU.S. Department of Veterans Affairs
KeywordsBooster (rocketry)VaccinationMedicineConfidence intervalBooster doseOdds ratioConfoundingInternal medicineImmunologyTiterVirus

Abstract

fetched live from OpenAlex

ABSTRACT Importance Previous studies have analyzed effectiveness of booster mRNA Covid-19 vaccination and compared it with 2-dose primary series for both Delta and Omicron variants. Observational studies that estimate effectiveness by comparing outcomes among vaccinated and unvaccinated individuals may suffer from residual confounding and exposure misclassification. Objective To estimate relative effectiveness of booster vaccination versus the 2-dose primary series with self-controlled study design Design, Setting and Participants We used the Veterans Health Administration (VHA) Corporate Data Warehouse to identify U.S. Veterans enrolled in care ≥2 years who received the 2-dose primary mRNA Covid-19 vaccine series and a mRNA Covid-19 booster following expanded recommendation for booster vaccination, and who had a positive SARS-CoV-2 test during the Delta (9/23/2021-11/30/2021) or Omicron (1/1/22-3/1/22) predominant period. Among them, we conducted a self-controlled risk interval (SCRI) analysis to compare odds of SARS-CoV-2 infection during a booster exposure interval versus a control interval. Exposures control interval (days 4-6 post-booster vaccination, presumably prior to gain of booster immunity), and booster exposure interval (days 14-16 post-booster vaccination, presumably following gain of booster immunity) Outcomes and Measures Positive PCR or antigen SARS-CoV-2 test. Separately for Delta and Omicron periods, we used conditional logistic regression to calculate odds ratios (OR) of a positive test for the booster versus control interval and calculated relative effectiveness of booster versus 2-dose primary series as (1-OR)*100. The SCRI approach implicitly controlled for time-fixed confounders. Results We found 42 individuals with a positive SARS-CoV-2 test in the control interval and 14 in the booster exposure interval during Delta period, and 137 and 66, respectively, in Omicron period. For the booster versus 2-dose primary series, the odds of infection were 70% (95%CI: 42%, 84%) lower during the Delta period and 56% (95%CI: 38%, 67%) lower during Omicron. Results were similar for ages <65 and ≥65 years in the Omicron period. In sensitivity analyses among those with prior Covid-19 history, and age stratification, ORs were similar to the main analysis. Conclusions Booster vaccination was more effective relative to a 2-dose primary series, the relative effectiveness was consistent across age groups and was higher during the Delta predominant period than during the Omicron period.

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)0.104
metaresearch head score (Gemma)0.147
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.548

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1040.147
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.012
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.044
GPT teacher head0.397
Teacher spread0.353 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2022
Admission routes1
Has abstractyes

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