Clinical and genomic signatures of SARS-CoV-2 Delta breakthrough infections in New York
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SciScore for 10.1101/2021.12.07.21267431: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: Study design and sample collection: This study was approved by the NYULH Institutional Review Board, protocol numbers i21-00493 and i21-00561. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis Statistical analysis: The comparison of 132 breakthrough and 283 unvaccinated control samples achieved 96% power in detecting a 15% difference (10% versus 25%) in mutation rates, clinical or demographic variables in a two-tailed chi squared/Fisher Exact test with a type I error of 5% (G*Power v. Table 2: Resources
Software and Algorithms Sentences Resources Statistical analysis: The comparison of 132 breakthrough and 283 unvaccinated control samples … SciScore for 10.1101/2021.12.07.21267431: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: Study design and sample collection: This study was approved by the NYULH Institutional Review Board, protocol numbers i21-00493 and i21-00561. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis Statistical analysis: The comparison of 132 breakthrough and 283 unvaccinated control samples achieved 96% power in detecting a 15% difference (10% versus 25%) in mutation rates, clinical or demographic variables in a two-tailed chi squared/Fisher Exact test with a type I error of 5% (G*Power v. Table 2: Resources
Software and Algorithms Sentences Resources Statistical analysis: The comparison of 132 breakthrough and 283 unvaccinated control samples achieved 96% power in detecting a 15% difference (10% versus 25%) in mutation rates, clinical or demographic variables in a two-tailed chi squared/Fisher Exact test with a type I error of 5% (G*Power v. G*Powersuggested: (G*Power, RRID:SCR_013726)The relationship between variant distribution and time since vaccination was studied using linear regression analyses in Prism v. Prismsuggested: (PRISM, RRID:SCR_005375)Results from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:As with all observational genomic surveillance studies, limitations and confounding factors exist. These include demographic, temporal, and behavioral factors, diagnostic testing practices, sequencing sensitivity thresholds, and sampling, e.g., undersampling of mild or asymptomatic cases. Some but not all of these factors can be adjusted or minimized by unbiased sample collection, consistent testing procedures and guidelines, and matched data analyses. Our adjusted model indicates that the probability of Delta infection has increased at similar rates in vaccinated and unvaccinated individuals. However, Delta breakthrough cases appear to rise continuously with extended time post vaccination (Fig. 5), which justifies the use of booster doses 52,53. Monitoring Delta, its evolving subvariants, and newly emerging variants including their early signs of adaptive evolution will be critical to adequately address upcoming SARS-CoV-2 outbreaks and the increasing numbers of vaccine breakthrough infections.
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.
- Thank you for including a protocol registration statement.
Results from scite Reference Check: We found no unreliable references.
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