Genomic epidemiology of SARS-CoV-2 transmission lineages in Ecuador

  1. Bernardo Gutierrez
  2. Sully Márquez
  3. Belén Prado-Vivar
  4. Mónica Becerra-Wong
  5. Juan José Guadalupe
  6. Darlan Da Silva Candido
  7. Juan Carlos Fernandez-Cadena
  8. Gabriel Morey-Leon
  9. Rubén Armas-Gonzalez
  10. Derly Madeleiny Andrade-Molina
  11. Alfredo Bruno
  12. Domenica De Mora
  13. Maritza Olmedo
  14. Denisse Portugal
  15. Manuel Gonzalez
  16. Alberto Orlando
  17. Jan Felix Drexler
  18. Andres Moreira-Soto
  19. Anna-Lena Sander
  20. Sebastian Brünink
  21. Arne Kühne
  22. Leandro Patiño
  23. Andrés Carrazco-Montalvo
  24. Orson Mestanza
  25. Jeannete Zurita
  26. Gabriela Sevillano
  27. Louis Du Plessis
  28. John T McCrone
  29. Josefina Coloma
  30. Gabriel Trueba
  31. Verónica Barragán
  32. Patricio Rojas-Silva
  33. Michelle Grunauer
  34. Moritz U G Kraemer
  35. Nuno R Faria
  36. Marina Escalera-Zamudio
  37. Oliver G Pybus
  38. Paúl Cárdenas

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Abstract

Characterisation of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic diversity through space and time can reveal trends in virus importation and domestic circulation and permit the exploration of questions regarding the early transmission dynamics. Here, we present a detailed description of SARS-CoV-2 genomic epidemiology in Ecuador, one of the hardest hit countries during the early stages of the coronavirus-19 pandemic. We generated and analysed 160 whole genome sequences sampled from all provinces of Ecuador in 2020. Molecular clock and phylogeographic analysis of these sequences in the context of global SARS-CoV-2 diversity enable us to identify and characterise individual transmission lineages within Ecuador, explore their spatiotemporal distributions, and consider their introduction and domestic circulation. Our results reveal a pattern of multiple international importations across the country, with apparent differences between key provinces. Transmission lineages were mostly introduced before the implementation of non-pharmaceutical interventions, with differential degrees of persistence and national dissemination.

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  1. Version published to 10.1093/ve/veab051
  2. ScreenIT

    SciScore for 10.1101/2021.03.31.21254685: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    UEES generated 33 whole genome sequences through Illumina sequencing on a MiniSeq platform (Illumina, San Diego, CA).
    MiniSeq
    suggested: None
    To determine the viral genetic diversity circulating in the country during the sampling period, all sequences from Ecuador were phylogenetically assigned under the global Pango lineage system using the Pangolin v2.2.2 tool (https://virological.org/t/pangolin-web-application-release/482).
    Pangolin
    suggested: None
    The tree for the systematically-subsampled data set was re-rooted by heuristically searching for the root placement that minimises the mean squared residual of a regression of sequence sample date against root-to-tip genetic distance, calculated using TempEst v1.5.3 (33), to maximise the temporal signal of the data set.
    TempEst
    suggested: (TempEst, RRID:SCR_017304)
    Parameter convergence was assessed using the effective sample size (ESS) estimates of the combined chains using Tracer v1.7.1 (37).
    Tracer
    suggested: (Tracer, RRID:SCR_019121)
    To identify nodes associated with transmission lineages in Ecuador, we used a discrete phylogeographic model consisting of a two-state discrete trait analysis (DTA) (40) implemented in BEAST v1.10.4 (34).
    BEAST
    suggested: (BEAST, RRID:SCR_010228)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The emergence of B.1.1 in Europe and North America around February 2020 (43) might suggest these regions contributed to seeding the epidemic in this province of Ecuador (despite the limitations on identifying exact source locations due to poor surveillance in many countries). B.1.1.74, the most prevalent lineage in Ecuador, is descended from B.1.1 and was more frequently sampled in Guayas during the early months of the epidemic (Fig S16), further revealing the role of locations where B.1.1 was prevalent as importation sources during the epidemic’s first wave. However, the high proportion of singletons observed in Guayas also suggests that onward transmission of introduced virus was less common. Insights from regions sampled at very high intensities, such as the United Kingdom, show that the majority of introductions lead to small, transient, dead-end transmission lineages, whereas a smaller number of introductions lead to larger and longer-lasting transmission lineages (15). If this phenomenon is a general property of the first wave of SARS-CoV-2 transmission, as appears to be the case given similar early observations in Brazil (5), Panama (48), Uruguay (49), Spain (50) and the Netherlands (51), we can expect that many of the introductions to Guayas led to few new cases, and that most of the ongoing transmission was derived from only a few introductions. The larger transmission lineages identified here suggest that virus transmission was high between neighbouring and well-con...

    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.
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    • No protocol registration statement was detected.

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  3. Version published to 10.1101/2021.03.31.21254685 on medRxiv