Viral loads and profile of the patients infected with SARS‐CoV‐2 Delta, Alpha, or R.1 variants in Tokyo

  1. Chihiro Tani‐Sassa
  2. Yumi Iwasaki
  3. Naoya Ichimura
  4. Katsutoshi Nagano
  5. Yuna Takatsuki
  6. Sonoka Yuasa
  7. Yuta Takahashi
  8. Jun Nakajima
  9. Kazunari Sonobe
  10. Yoko Nukui
  11. Hiroaki Takeuchi
  12. Kousuke Tanimoto
  13. Yukie Tanaka
  14. Akinori Kimura
  15. Shuji Tohda

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Abstract

The rapid spread of the Delta variant of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) became a serious concern worldwide in summer 2021. We examined the copy number and variant types of all SARS‐CoV‐2‐positive patients who visited our hospital from February to August 2021 using polymerase chain reaction (PCR) tests. Whole genome sequencing was performed for some samples. The R.1 variant (B.1.1.316) was responsible for most infections in March, replacing the previous variant (B.1.1.214); the Alpha (B.1.1.7) variant caused most infections in April and May; and the Delta variant (B.1.617.2) was the most prevalent in July and August. There was no significant difference in the copy numbers among the previous variant cases ( n  = 29, median 3.0 × 10 4 copies/µl), R.1 variant cases ( n  = 28, 2.1 × 10 5 copies/µl), Alpha variant cases ( n  = 125, 4.1 × 10 5 copies/µl), and Delta variant cases ( n  = 106, 2.4 × 10 5 copies/µl). Patients with Delta variant infection were significantly younger than those infected with R.1 and the previous variants, possibly because many elderly individuals in Tokyo were vaccinated between May and August. There was no significant difference in mortality among the four groups. Our results suggest that the increased infectivity of Delta variant may be caused by factors other than the higher viral loads. Clarifying these factors is important to control the spread of Delta variant infection.

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  1. Version published to 10.1002/jmv.27479
  2. ScreenIT

    SciScore for 10.1101/2021.09.21.21263879: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: This study was approved by the Medical Research Ethics Committee of Tokyo Medical and Dental University (approval number: M2020-004) and was conducted in accordance with the ethical standards of the 1964 Helsinki Declaration.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Whole genome sequencing (WGS) was performed to identify the lineages of representative samples using a next-generation sequencer.
    WGS
    suggested: None
    Libraries were prepared using the QIAseq SARS-CoV-2 Primer Panel Kit (QIAGEN) and sequenced using the MiSeq (Illumina, Inc.; San Diego, USA).
    MiSeq
    suggested: (A5-miseq, RRID:SCR_012148)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.09.21.21263879v1 on medRxiv