δ subvariants of SARS-COV-2 in Israel, Qatar and Bahrain: Optimal vaccination as an effective strategy to block viral evolution and control the pandemic

  1. Xiang-Jiao Yang

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Abstract

δ variant has rapidly become the predominant pandemic driver and yielded four subvariants (δ1, δ2, δ3 and δ4). Among them, δ1 has been mainly responsible for the latest COVID-19 waves in India, Southeast Asia, Europe and the USA. A relevant question is how δ subvariants may have driven the pandemic in the rest of the world. In both Israel and Qatar, mRNA-based vaccination has been rolled out competitively, but the outcomes are quite different in terms of controlling the recent waves resulting from δ variant. This raises the question whether δ subvariants have acted differently in Israel and Qatar. In both countries, δ variant was first identified in April 2021 and δ1 subvariant constituted ∼50% δ genomes from April to May 2021. But the situation started to diverge in June 2021: In Israel, δ1 variant was encoded by 92.0% δ genomes, whereas this fraction was only 43.9% in Qatar. Moreover, a δ1 sublineage encoding spike T791I was identified in Israel but not Qatar. This sublineage accounted for 31.8% δ genomes sequenced in June 2021 and declined to 13.3% in October 2021. In August 2021, δ1 also became dominant in Qatar and a major sublineage encoding spike D1259H emerged. This sublineage has evolved further and acquired additional spike substitutions, including K97E, S255F, I693S, I712S, I1104L, E1258D and/or V1177I, in Qatar and other countries, such as Czech Republic, France and Mexico. Monthly distribution of the above sublineages suggests that the one from Qatar is much more of concern than that from Israel. Different from what was in Israel and Qatar, δ2 subvariant has also been important in Bahrain, whereas a δ2 sublineage encoding spike V1264L and A1736V of NSP3 was dominant in June 2021, but was gradually taken over by δ1 subvariant. These results suggest that δ1 and δ2 subvariants continue their evolution in different countries. The recent successful pandemic control in Israel, Qatar and Bahrain supports that δ1 and δ2 subvariants are still sensitive to timed vaccination, thereby urging the use of optimal immunity as a strategy to block SARS-COV-2 evolution and control the pandemic.

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    SciScore for 10.1101/2021.11.01.21265445: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Two cleaned Fasta files were also uploaded onto SnapGene (version 5.3.2) for multisequence alignment via the MAFFT tool, and RAxML-NG version 0.9.0 [14] was used for subsequent phylogenetic analysis as described [15].
    SnapGene
    suggested: (SnapGene, RRID:SCR_015052)
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    PyMol structural modeling: The PyMol molecular graphics system (version 2.4.2, https://pymol.org/2/) from Schrödinger, Inc. was used for downloading structure files from the PDB database for further analysis and image generation.
    PyMol
    suggested: (PyMOL, RRID:SCR_000305)
    Structural images were cropped via Adobe Photoshop for further presentation through Illustrator.
    Adobe Photoshop
    suggested: (Adobe Photoshop, RRID:SCR_014199)
    Pandemic and vaccination data: Pandemic and vaccination data were downloaded from the Our World in Data website (https://ourworldindata.org/explorers/coronavirus-data-explorer?zoomToSelection=true&time=2020-03-01..latest&facet=none&pickerSort=desc&pickerMetric=total_cases&Metric=Confirmed+cases&Interval=Cumulative&Relative+to+Population=false&Align+outbreaks=false&country=∼OWID_WRL) as a .csv file for further processing via Excel and figure generation through Prism 9.0 and Adobe Illustrator.
    Excel
    suggested: None
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    Adobe Illustrator
    suggested: (Adobe Illustrator, RRID:SCR_010279)

    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.

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  2. Version published to 10.1101/2021.11.01.21265445v1 on medRxiv