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Reviews of "Variants in SARS-CoV-2 Associated with Mild or Severe Outcome"

Reviewers: Min Xie (Harvard) | 📒📒📒◻️◻️ • Hebah Al Khatib (UC Berkeley) | 📒📒📒◻️◻️

Published onJul 05, 2021
Reviews of "Variants in SARS-CoV-2 Associated with Mild or Severe Outcome"
key-enterThis Pub is a Review of
Variants in SARS-CoV-2 Associated with Mild or Severe Outcome
Description

AbstractIntroductionThe coronavirus disease 2019 (COVID-19) pandemic is a global public health emergency causing a disparate burden of death and disability around the world. The molecular characteristics of the virus that predict better or worse outcome are largely still being discovered.MethodsWe downloaded 155,958 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from GISAID and evaluated whether variants improved prediction of reported severity beyond age and region. We also evaluated specific variants to determine the magnitude of association with severity and the frequency of these variants among the genomes.ResultsLogistic regression models that included viral genomic variants outperformed other models (AUC=0.91 as compared with 0.68 for age and gender alone; p<0.001). Among individual variants, we found 17 single nucleotide variants in SARS-CoV-2 have more than two-fold greater odds of being associated with higher severity and 67 variants associated with ≤ 0.5 times the odds of severity. The median frequency of associated variants was 0.15% (interquartile range 0.09%-0.45%). Altogether 85% of genomes had at least one variant associated with patient outcome.ConclusionNumerous SARS-CoV-2 variants have two-fold or greater association with odds of mild or severe outcome and collectively, these variants are common. In addition to comprehensive mitigation efforts, public health measures should be prioritized to control the more severe manifestations of COVID-19 and the transmission chains linked to these severe cases.

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Summary of Reviews: This preprint reports viral variants can improve the classification of COVID-19 outcomes as compared with models using only age and region, with some individual variants associated with disease severity. Reviewers suggest major revisions to improve and clarify data analysis.

Reviewer 1 (Min Xie) | 📒📒📒 ◻️◻️

Reviewer 2 (Hebah Al Khatib) | 📒📒📒 ◻️◻️

RR:C19 Strength of Evidence Scale Key

📕 ◻️◻️◻️◻️ = Misleading

📙📙 ◻️◻️◻️ = Not Informative

📒📒📒 ◻️◻️ = Potentially Informative

📗📗📗📗◻️ = Reliable

📘📘📘📘📘 = Strong

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