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Review 1: "Variants in SARS-CoV-2 Associated with Mild or Severe Outcome"

This preprint reports viral variants can improve 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.

Published onJul 05, 2021
Review 1: "Variants in SARS-CoV-2 Associated with Mild or Severe Outcome"
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key-enterThis Pub is a Review of
Variants in SARS-CoV-2 Associated with Mild or Severe Outcome

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.

RR:C19 Evidence Scale rating by reviewer:

  • Potentially informative. The main claims made are not strongly justified by the methods and data, but may yield some insight. The results and conclusions of the study may resemble those from the hypothetical ideal study, but there is substantial room for doubt. Decision-makers should consider this evidence only with a thorough understanding of its weaknesses, alongside other evidence and theory. Decision-makers should not consider this actionable, unless the weaknesses are clearly understood and there is other theory and evidence to further support it.



The authors evaluated the association of SARS-COV-2 variants with the severity of COVID-19 from the database of GISAID. The topic is interesting to the readers especially considering the current epidemic involved with several new SARS-COV-2 variant strains. While there are still some major concerns:

1. Although the authors stressed the big number of 155,958 SARS-COV-2 genomes downloaded from GISAID database, only 3637 sequences were evaluated in this study according to the aims and method stated in the manuscript. The big gap draws attention to whether the results of this study could be representative of the actual prevalent variants around the world.

2. Generally, COVID-19 patients would consist of around 80% mild cases and 20% severe cases. While in this study, the population had 2870 severe cases and 767 mild cases. The reason may due to the higher probability of severe cases to be tested for virus genome. However, the imbalance of the severe/mild ratio would lead to the bias of the result, especially considering the statistical complexity.

3. When evaluating the severity of COVID-19, the criteria are extremely important and critical for the interpretation of the results. In this study, the severe cases included “deceased,” “hospitalized,” “ICU,” and “pneumonia.” It would be quite confusing. For example, COVID-19 pneumonia could be a mild disease in clinical practice. Another concern is some COVID-19 patients were hospitalized because of their underlying disease, while not for the severe COVID-19 condition. Such issues happened frequently in nursing homes or with elderly patients. Thus, the authors need to address a clear definition of severe COVID-19 and make an appropriate classification of subjects.

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