What is the uncertainty in efficacy of COVID-19 vaccines? A Bayesian analysis
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Abstract
This short paper reports a Bayesian analysis of the publicly available COVID-19 trial results. The analysis casts some doubts on whether the half+full dose regime of the AstraZeneca COVID-19 vaccine is truly more effective than the 2x full dose regime. The 95% posterior interval for the efficacy of the half+full dose regime is 66.6-96.3%, while for the 2x full dose regime it is 39.0-74.8%. Hence, it is possible that in both dosage regimes the vaccine has similar efficacy, around 70%. The estimated efficacy for the Pfizer vaccine is 89.9-97.4% and for Moderna 86.3-97.5%. These results should be interpreted with care though, since this analysis does not account for differences in for instance trial population, COVID-19 testing, and storage requirements for the various vaccines.
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SciScore for 10.1101/2020.11.30.20240671: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.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:It comes with several limitations. Most notably, not taken into account is that vaccines and trials can differ in many ways, such as: The analysis could also be further extended. For instance, hierarchical priors could be used across different trials in order to get a sense of the distribution of vaccine efficacy. Also, a more formal …
SciScore for 10.1101/2020.11.30.20240671: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.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:It comes with several limitations. Most notably, not taken into account is that vaccines and trials can differ in many ways, such as: The analysis could also be further extended. For instance, hierarchical priors could be used across different trials in order to get a sense of the distribution of vaccine efficacy. Also, a more formal Bayesian analysis could be performed to assess the posterior probability of the difference in efficacy of the two dosage regimes of the AstraZeneca vaccine. Such analysis could use earlier trial results with different dosage regimes (from COVID-19 or other vaccines) and/or expert assessments to estimate the prior probability that a half+full dose regime would be more effective than a 2x full dose regime. Finally, inference can be improved as more data comes available on these and other vaccines. Appendix A contains the R code used for the present analysis, which future researchers can use for replication of the results in this paper and for future extensions.
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.
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