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Record W3176572599 · doi:10.1101/2021.06.29.21255526

Transmissibility of COVID-19 among Vaccinated Individuals: A Rapid Literature Review - Update #1

2021· preprint· en· W3176572599 on OpenAlexaff
Oluwaseun Egunsola, Liza Mastikhina, Laura E. Dowsett, Brenlea Farkas, Mark Hofmeister, Lynora Saxinger, Fiona Clement

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of AlbertaSouth Health Campus
Fundersnot available
KeywordsObservational studyVaccinationMedicineAsymptomaticRandomized controlled trialTransmission (telecommunications)Vaccine efficacyPopulationSystematic reviewClinical trialMEDLINEIntensive care medicinePediatricsVirologyInternal medicineEnvironmental healthBiology

Abstract

fetched live from OpenAlex

Abstract Objectives This is an update of a previous report that examined literature published up to March 11th, 2021. Sixteen additional studies have been included in this update. The objective of this report is to identify comparative observational studies and randomized controlled trials (RCTs) evaluating the efficacy and effectiveness of COVID-19 vaccination in reducing forward transmission from vaccinated people, and studies examining the biological plausibility of vaccination-induced transmission reduction. Method A search of databases, MEDLINE, Embase, L-OVE and the Cochrane Central Register of Controlled Trials was conducted to identify RCTs or comparative observational studies evaluating the efficacy and effectiveness of COVID-19 vaccination in the prevention of transmission, asymptomatic infections and transmissibility of COVID-19 among vaccinated persons. An additional search of grey literature was conducted. This search is current to May 4th, 2021. Results In this update, 16 additional studies, including 9 human and 7 animal studies, were included. Therefore, this review examines a total of 33 included studies: 21 human studies and 12 preclinical animal studies. Evidence from two large household surveillance studies from the UK suggests that a single or full dose of AstraZeneca (AZ) and Pfizer-BioNtech (PfBnT) vaccines may prevent household transmission of COVID-19 after 14 days of vaccination by up to 54%. The AZ vaccine trials in the general population suggest that an initial low dose followed by a standard dose may provide up to 59% protection against asymptomatic or unknown infection, although efficacy against these outcomes was not demonstrated following two standard doses. PfBnT vaccine observational studies in the general population suggest up to 90% effectiveness against asymptomatic infection after seven or more days of full dose vaccination. Up to 75% effectiveness against asymptomatic infection was reported after full- dose in healthcare workers. Across RCTs examining asymptomatic infection in the general population, one dose of Moderna was shown to provide an efficacy of 61.4% against asymptomatic infection 21 days after the first dose; in another trial, the J&J vaccine had an efficacy of 74% 28 days after the first dose. Lastly, seven of eight studies found significantly increased cycle threshold, suggestive of lower viral load, in PfBnT or AZ vaccinated individuals compared with those who were unvaccinated. Conclusion The AZ and PfBnT vaccines may prevent household transmission of COVID-19 after 14 days of vaccination. More studies have found the vaccines to significantly reduce the risk of asymptomatic infection and significantly increase cycle threshold, suggestive of lower viral load. Further research is needed to evaluate post-vaccination infectivity and transmission of both the wild type COVID-19 virus and the variants of concern from other jurisdictions.

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)0.007
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0220.016
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.049
GPT teacher head0.373
Teacher spread0.324 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations4
Published2021
Admission routes1
Has abstractyes

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