Multiple early introductions of SARS-CoV-2 into a global travel hub in the Middle East

  1. Ahmad Abou Tayoun
  2. Tom Loney
  3. Hamda Khansaheb
  4. Sathishkumar Ramaswamy
  5. Divinlal Harilal
  6. Zulfa Omar Deesi
  7. Rupa Murthy Varghese
  8. Hanan Al Suwaidi
  9. Abdulmajeed Alkhajeh
  10. Laila Mohamed AlDabal
  11. Mohammed Uddin
  12. Rifat Hamoudi
  13. Rabih Halwani
  14. Abiola Senok
  15. Qutayba Hamid
  16. Norbert Nowotny
  17. Alawi Alsheikh-Ali

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Abstract

International travel played a significant role in the early global spread of SARS-CoV-2. Understanding transmission patterns from different regions of the world will further inform global dynamics of the pandemic. Using data from Dubai in the United Arab Emirates (UAE), a major international travel hub in the Middle East, we establish SARS-CoV-2 full genome sequences from the index and early COVID-19 patients in the UAE. The genome sequences are analysed in the context of virus introductions, chain of transmissions, and possible links to earlier strains from other regions of the world. Phylogenetic analysis showed multiple spatiotemporal introductions of SARS-CoV-2 into the UAE from Asia, Europe, and the Middle East during the early phase of the pandemic. We also provide evidence for early community-based transmission and catalogue new mutations in SARS-CoV-2 strains in the UAE. Our findings contribute to the understanding of the global transmission network of SARS-CoV-2.

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  1. Version published to 10.1038/s41598-020-74666-w
  2. Version published to 10.1101/2020.05.06.080606v4 on bioRxiv
  3. Version published to 10.1101/2020.05.06.080606v3 on bioRxiv
  4. ScreenIT

    SciScore for 10.1101/2020.05.06.080606: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the Dubai Scientific Research Ethics Committee - Dubai Health Authority (approval number #DSREC-04/2020_02).
    Consent: The requirement for informed consent was waived as this study was part of a public health surveillance and outbreak investigation in the UAE.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All 182 sequences, including the 25 UAE sequences generated in this study, were analysed using Nexstrain [10], which consists of Augur v6.4.3 pipeline for multiple sequence alignment (MAFFT v7.455 [11]) and phylogenetic tree construction (IQtree v1.6.12 [12]).
    Augur
    suggested: None
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Tree visualization and annotations were performed in FigTree v1.4.4 [13] for Figure 1 and in auspice v2.13.0 tool [10] for Figure 2.
    FigTree
    suggested: (FigTree, RRID:SCR_008515)

    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: We detected the following sentences addressing limitations in the study:
    Limitations included the inability to conduct full whole genome sequencing on more samples most likely due to low viral load issues, although we were able to deduce the origin of transmission in most of those individuals based on travel history. Regardless, this study contributes important molecular epidemiological data that can be used to further understand the global transmission network of SARS-CoV-2 [8].

    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.

    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.

  5. Version published to 10.1101/2020.05.06.080606v2 on bioRxiv
  6. Version published to 10.1101/2020.05.06.080606v1 on bioRxiv