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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 OpenAlexafffundabout
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

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

OBJECTIVE: To estimate the effectiveness of mRNA covid-19 vaccines against symptomatic infection and severe outcomes (hospital admission or death). DESIGN: Test negative design study. SETTING: Ontario, Canada between 14 December 2020 and 19 April 2021. PARTICIPANTS: 324 033 community dwelling people aged ≥16 years who had symptoms of covid-19 and were tested for SARS-CoV-2. INTERVENTIONS: BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna) vaccine. MAIN OUTCOME MEASURES: Laboratory confirmed SARS-CoV-2 by reverse transcription polymerase chain reaction (RT-PCR) and hospital admissions and deaths associated with SARS-CoV-2 infection. Multivariable logistic regression was adjusted for personal and clinical characteristics associated with SARS-CoV-2 and vaccine receipt to estimate vaccine effectiveness against symptomatic infection and severe outcomes. RESULTS: Of 324 033 people with symptoms, 53 270 (16.4%) were positive for SARS-CoV-2 and 21 272 (6.6%) received at least one dose of vaccine. Among participants who tested positive, 2479 (4.7%) were admitted to hospital or died. Vaccine effectiveness against symptomatic infection observed ≥14 days after one dose was 60% (95% confidence interval 57% to 64%), increasing from 48% (41% to 54%) at 14-20 days after one dose to 71% (63% to 78%) at 35-41 days. Vaccine effectiveness observed ≥7 days after two doses was 91% (89% to 93%). Vaccine effectiveness against hospital admission or death observed ≥14 days after one dose was 70% (60% to 77%), increasing from 62% (44% to 75%) at 14-20 days to 91% (73% to 97%) at ≥35 days, whereas vaccine effectiveness observed ≥7 days after two doses was 98% (88% to 100%). For adults aged ≥70 years, vaccine effectiveness estimates were observed to be lower for intervals shortly after one dose but were comparable to those for younger people for all intervals after 28 days. After two doses, high vaccine effectiveness was observed against variants with the E484K mutation. CONCLUSIONS: Two doses of mRNA covid-19 vaccines were observed to be highly effective against symptomatic infection and severe outcomes. Vaccine effectiveness of one dose was observed to be 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.

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)0.004
metaresearch head score (Gemma)0.007
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 score0.068
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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

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

Citations51
Published2021
Admission routes3
Has abstractyes

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