Effectiveness of Coronavirus Disease 2019 Vaccines Against Hospitalization and Death in Canada: A Multiprovincial, Test-Negative Design Study
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Abstract
Background
A major goal of coronavirus disease 2019 (COVID-19) vaccination is to prevent severe outcomes (hospitalizations and deaths). We estimated the effectiveness of messenger RNA (mRNA) and ChAdOx1 COVID-19 vaccines against severe outcomes in 4 Canadian provinces between December 2020 and September 2021.
Methods
We conducted this multiprovincial, retrospective, test-negative study among community-dwelling adults aged ≥18 years in Ontario, Quebec, British Columbia, and Manitoba using linked provincial databases and a common study protocol. Multivariable logistic regression was used to estimate province-specific vaccine effectiveness against COVID-19 hospitalization and/or death. Estimates were pooled using random-effects models.
Results
We included 2 508 296 tested participants, with 31 776 COVID-19 hospitalizations and 5842 deaths. Vaccine effectiveness was 83% after a first dose and 98% after a second dose against both hospitalization and death (separately). Against severe outcomes, effectiveness was 87% (95% confidence interval [CI], 71%–94%) ≥84 days after a first dose of mRNA vaccine, increasing to 98% (95% CI, 96%–99%) ≥112 days after a second dose. Vaccine effectiveness against severe outcomes for ChAdOx1 was 88% (95% CI, 75%–94%) ≥56 days after a first dose, increasing to 97% (95% CI, 91%–99%) ≥56 days after a second dose. Lower 1-dose effectiveness was observed for adults aged ≥80 years and those with comorbidities, but effectiveness became comparable after a second dose. Two doses of vaccines provided very high protection for both homologous and heterologous schedules and against Alpha, Gamma, and Delta variants.
Conclusions
Two doses of mRNA or ChAdOx1 vaccine provide excellent protection against severe outcomes.
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SciScore for 10.1101/2022.04.13.22273825: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization For controls with multiple negative tests, we randomly selected one symptomatic test-negative specimen collection date. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This study has some limitations. First, while the test-negative design accounts for differences in healthcare seeking behaviour, indications for …
SciScore for 10.1101/2022.04.13.22273825: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization For controls with multiple negative tests, we randomly selected one symptomatic test-negative specimen collection date. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This study has some limitations. First, while the test-negative design accounts for differences in healthcare seeking behaviour, indications for testing and risks of exposure to SARS-CoV-2 infection between test-positive cases and test-negative controls may differ. Testing indications also varied between the provinces and over the study period. We adjusted for biweekly period of test and number of prior tests to account for these. Second, although healthcare utilization and thresholds for hospitalization may vary between and within jurisdictions, hospital capacity was maintained to admit patients requiring hospitalization and we do not expect differential under-or over-estimation of severe outcomes, particularly death, with respect to COVID-19 vaccination status. Third, despite a common study protocol, there is likely heterogeneity among provinces in terms of differences in populations, vaccination programs (rollout logistics and priority groups), SARS-CoV-2 testing criteria, data capture, and covariates adjusted; we used random-effects models to account for statistical heterogeneity. Fourth, given the observational nature of the study, residual confounding remains possible despite adjustment for a number of potential confounders. Finally, our VE estimates may not apply to severe outcomes caused by Omicron. In conclusion, our results from this large multiprovincial study provide strong evidence of excellent protection against severe outcomes of hospitalizations and deaths wit...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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