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Record W3207338245 · doi:10.1101/2021.05.24.21257744

Effectiveness of BNT162b2 and mRNA-1273 COVID-19 vaccines against symptomatic SARS-CoV-2 infection and severe COVID-19 outcomes in Ontario, Canada: a test-negative design study

2021· preprint· en· W3207338245 on OpenAlex
Hannah Chung, Siyi He, Sharifa Nasreen, Maria E. Sundaram, Sarah A. Buchan, Sarah E. Wilson, Branson Chen, Andrew Calzavara, Deshayne B. Fell, Peter C. Austin, Kumanan Wilson, Kevin L. Schwartz, Kevin A. Brown, Jonathan B. Gubbay, Nicole E. Basta, Salaheddin M. Mahmud, Christiaan H. Righolt, Lawrence W. Svenson, Shannon E. MacDonald, Naveed Z. Janjua, Mina Tadrous, Jeffrey C. Kwong

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity Health NetworkWomen's College HospitalUniversity of AlbertaBC Centre for Disease ControlAlberta HealthUniversity of ManitobaUniversity of CalgaryUniversity of OttawaMcGill UniversityChildren's Hospital of Eastern OntarioBruyèreUniversity of British ColumbiaPublic Health OntarioUniversity of Toronto
FundersDepartment of Family and Community Medicine, University of TorontoCanadian Institutes of Health ResearchCanadian Immunization Research NetworkUniversity of TorontoPublic Health AgencyPublic Health Agency of CanadaHeart and Stroke Foundation of Canada
KeywordsMedicineCoronavirus disease 2019 (COVID-19)VaccinationSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Logistic regressionInternal medicinePediatricsImmunologyDisease

Abstract

fetched live from OpenAlex

ABSTRACT Objectives To estimate the effectiveness of mRNA COVID-19 vaccines against symptomatic infection and severe outcomes. Design We applied a test-negative design study to linked laboratory, vaccination, and health administrative databases, and used multivariable logistic regression adjusting for demographic and clinical characteristics associated with SARS-CoV-2 and vaccine receipt to estimate vaccine effectiveness (VE) against symptomatic infection and severe outcomes. Setting Ontario, Canada between 14 December 2020 and 19 April 2021. Participants Community-dwelling adults aged ≥16 years who had COVID-19 symptoms and were tested for SARS-CoV-2. Interventions Pfizer-BioNTech’s BNT162b2 or Moderna’s mRNA-1273 vaccine. Main outcome measures Laboratory-confirmed SARS-CoV-2 by RT-PCR; hospitalization/death associated with SARS-CoV-2 infection. Results Among 324,033 symptomatic individuals, 53,270 (16.4%) were positive for SARS-CoV-2 and 21,272 (6.6%) received ≥1 vaccine dose. Among test-positive cases, 2,479 (4.7%) had a severe outcome. VE against symptomatic infection ≥14 days after receiving only 1 dose was 60% (95%CI, 57 to 64%), increasing from 48% (95%CI, 41 to 54%) at 14–20 days after the first dose to 71% (95%CI, 63 to 78%) at 35–41 days. VE ≥7 days after 2 doses was 91% (95%CI, 89 to 93%). Against severe outcomes, VE ≥14 days after 1 dose was 70% (95%CI, 60 to 77%), increasing from 62% (95%CI, 44 to 75%) at 14–20 days to 91% (95%CI, 73 to 97%) at ≥35 days, whereas VE ≥7 days after 2 doses was 98% (95%CI, 88 to 100%). For adults aged ≥70 years, VE estimates were lower for intervals shortly after receiving 1 dose, but were comparable to younger adults for all intervals after 28 days. After 2 doses, we observed high VE against E484K-positive variants. Conclusions Two doses of mRNA COVID-19 vaccines are highly effective against symptomatic infection and severe outcomes. Single-dose effectiveness is lower, particularly for older adults shortly after the first dose.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.351
Teacher spread0.293 · 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