Genomic Epidemiology of SARS-CoV-2 in Seychelles, 2020–2021

  1. John Mwita Morobe
  2. Brigitte Pool
  3. Lina Marie
  4. Dwayne Didon
  5. Arnold W. Lambisia
  6. Timothy Makori
  7. Khadija Said Mohammed
  8. Zaydah R. de Laurent
  9. Leonard Ndwiga
  10. Maureen W. Mburu
  11. Edidah Moraa
  12. Nickson Murunga
  13. Jennifer Musyoki
  14. Jedida Mwacharo
  15. Lydia Nyamako
  16. Debra Riako
  17. Pariken Ephnatus
  18. Faith Gambo
  19. Josephine Naimani
  20. Joyce Namulondo
  21. Susan Zimba Tembo
  22. Edwin Ogendi
  23. Thierno Balde
  24. Fred Athanasius Dratibi
  25. Ali Ahmed Yahaya
  26. Nicksy Gumede
  27. Rachel A. Achilla
  28. Peter K. Borus
  29. Dorcas W. Wanjohi
  30. Sofonias K. Tessema
  31. Joseph Mwangangi
  32. Philip Bejon
  33. David J. Nokes
  34. Lynette Isabella Ochola-Oyier
  35. George Githinji
  36. Leon Biscornet
  37. Charles N. Agoti

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Abstract

Seychelles, an archipelago of 155 islands in the Indian Ocean, had confirmed 24,788 cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the 31st of December 2021. The first SARS-CoV-2 cases in Seychelles were reported on the 14th of March 2020, but cases remained low until January 2021, when a surge was observed. Here, we investigated the potential drivers of the surge by genomic analysis of 1056 SARS-CoV-2 positive samples collected in Seychelles between 14 March 2020 and 31 December 2021. The Seychelles genomes were classified into 32 Pango lineages, 1042 of which fell within four variants of concern, i.e., Alpha, Beta, Delta and Omicron. Sporadic cases of SARS-CoV-2 detected in Seychelles in 2020 were mainly of lineage B.1 (lineage predominantly observed in Europe) but this lineage was rapidly replaced by Beta variant starting January 2021, and which was also subsequently replaced by the Delta variant in May 2021 that dominated till November 2021 when Omicron cases were identified. Using the ancestral state reconstruction approach, we estimated that at least 78 independent SARS-CoV-2 introduction events occurred in Seychelles during the study period. The majority of viral introductions into Seychelles occurred in 2021, despite substantial COVID-19 restrictions in place during this period. We conclude that the surge of SARS-CoV-2 cases in Seychelles in January 2021 was primarily due to the introduction of more transmissible SARS-CoV-2 variants into the islands.

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  1. Version published to 10.3390/v14061318
  2. Version published to 10.1101/2022.03.18.22272503v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2022.03.18.22272503: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The whole genome sequencing study protocol was reviewed and approved by the Scientific and Ethics Review Committee (SERU) at KEMRI, (SERU #4035).
    Consent: Individual patient consent requirement was waivered by the committee as the sequenced samples were part of the public health emergency response.
    Sex as a biological variablenot detected.
    RandomizationTo ensure global representation of sequences, we downloaded all the sequences (n= 8,916,634) from the Global Initiative on Sharing All Influenza Data (GISAID) database collected before 31st December and used an in-house R script to randomly select a sub-sample of 5,179 genomes while considering Pango lineage (lineages detected in Seychelles only), continent and date of collection.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The final library was normalised to 15-70 ng, loaded on a SpotON R9 flow cell and sequenced on a MinION Mk1B or GridION device5.
    MinION
    suggested: (MinION, RRID:SCR_017985)
    The consensus sequences were then polished using Nanopolish toolkit (version 0.13.3) using the raw signals.
    Nanopolish
    suggested: (Nanopolish, RRID:SCR_016157)
    A maximum likelihood (ML) phylogeny was inferred using IQTREE version 2.1.3 (http://www.iqtree.org/).
    http://www.iqtree.org/
    suggested: (IQ-TREE, RRID:SCR_017254)
    The resulting trees were visualized using the Bioconductor ggTree version 2.2.4 package9 in R10.
    Bioconductor
    suggested: (Bioconductor, RRID:SCR_006442)
    Using the date and location annotated tree topology, we counted the number of transitions between Seychelles and the rest of the world and plotted this using ggplot2 version 3.3.3 12.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    Results from OddPub: Thank you for sharing your code.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    This study had some limitations. First, our import/export inferences can be influenced by sampling biases and low rate of sequencing in Seychelles. Therefore, the true number of international introductions are likely significantly higher than what is reported here. Second, incomplete metadata for some samples limited the scope of our analysis, for example, lack of location of sample collected disallowed us to investigate the transmission pathway of viruses within the country. Third, SARS-CoV-2 sequences from Seychelles are only available from a very small fraction of the number of confirmed cases into the country. These data reinforce the importance of genomic surveillance in Seychelles as a tool for monitoring and providing real-time information on spread of emerging SARS-CoV-2 variants in the population with important implications for public health and immunization strategies. Surge of COVID-19 cases due VOCs during a period of heightened COVID-19 countermeasures raises questions on the optimal timing of the introduction of public health interventions. When the interventions are introduced after a surge has started, it is often too late, and the control strategies should focus on local transmission to understand characteristics and origins of locally circulating SARS-CoV-2 diversity to prevent further spread. Moreover, studies on genomic surveillance would also be useful in investigating vaccine effectiveness against circulating variants which appear to have a high turnover...

    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.

  4. Version published to 10.1101/2022.03.18.22272503v1 on medRxiv