Spatiotemporal analyses illuminate the competitive advantage of a SARS-CoV-2 variant of concern over a variant of interest

  1. Alexis Russell
  2. Collin O’Connor
  3. Erica Lasek-Nesselquist
  4. Jonathan Plitnick
  5. John P. Kelly
  6. Daryl M. Lamson
  7. Kirsten St. George

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Abstract

The emergence of novel SARS-CoV-2 variants in late 2020 and early 2021 raised alarm worldwide and prompted reassessment of the management, surveillance, and projected future of COVID-19. Mutations that confer competitive advantages by increasing transmissibility or immune evasion have been associated with the localized dominance of single variants. Thus, elucidating the evolutionary and epidemiological dynamics among novel variants is essential for understanding the trajectory of the COVID-19 pandemic. Here we show the interplay between B.1.1.7 (Alpha) and B.1.526 (Iota) in New York (NY) from December 2020 to April 2021 through phylogeographic analyses, space-time scan statistics, and cartographic visualization. Our results indicate that B.1.526 likely evolved in the Bronx in late 2020, providing opportunity for an initial foothold in the heavily interconnected New York City (NYC) region, as evidenced by numerous exportations to surrounding locations. In contrast, B.1.1.7 became dominant in regions of upstate NY where B.1.526 had limited presence, suggesting that B.1.1.7 was able to spread more efficiently in the absence of B.1.526. Clusters discovered from the spatial-time scan analysis supported the role of competition between B.1.526 and B.1.1.7 in NYC in March 2021 and the outsized presence of B.1.1.7 in upstate NY in April 2021. Although B.1.526 likely delayed the rise of B.1.1.7 in NYC, B.1.1.7 became the dominant variant in the Metro region by the end of the study period. These results reveal the advantages endemicity may grant to a variant (founder effect), despite the higher fitness of an introduced lineage. Our research highlights the dynamics of inter-variant competition at a time when B.1.617.2 (Delta) is overtaking B.1.1.7 as the dominant lineage worldwide. We believe our combined spatiotemporal methodologies can disentangle the complexities of shifting SARS-CoV-2 variant landscapes at a time when the evolution of variants with additional fitness advantages is impending.

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  1. ScreenIT

    SciScore for 10.1101/2021.09.14.21262977: (What is this?)

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

    Table 1: Rigor

    EthicsField Sample Permit: Illumina libraries were processed with ARTIC nextflow pipelines (github.com/connorlab/ncov2019/articnf/tree/illumine, last updated April 2020) as previously described (Alpert et al., 2021; supplementary information) Sample inclusion criteria: Specimens with collection dates between December 1, 2020 and April 30, 2021 were included.
    Sex as a biological variablenot detected.
    RandomizationPhylogeographic analyses: All B.1.526 genomes from the United States (US) and associated metadata (excluding NY sequences) were downloaded from GISAID (GISAID.org) and randomly subsampled to approximately equal depth as the heaviest sampled NY region in our dataset, with the number of genomes from each state sampled proportionally to their overall frequency in the US.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    This tree served as the fixed tree for ancestral state reconstruction in Beast v2.6.2 (40) to infer timing and source of B.1.526 introductions within the state of NY.
    Beast
    suggested: (BEAST, RRID:SCR_010228)
    A B.1.1.7 phylogeographic analysis was conducted in the same manner with the states inferred for a fixed topology over 6 million generations in BEAST2 under an exponential coalescent model until all ESS reach >= 200.
    BEAST2
    suggested: (BEAST2, RRID:SCR_017307)
    The number of introductions between locations was summarized by Baltic (https://github.com/evogytis/baltic) by adopting the exploded tree script for Python 3.
    Python
    suggested: (IPython, RRID:SCR_001658)
    Trees were visualized in FigTree v1.5.5 (http://tree.bio.ed.ac.uk/software/figtree/) and ggtree (41) for R v4.1.0 (http://www.R-project.org) (see supplementary information for additional details).
    FigTree
    suggested: (FigTree, RRID:SCR_008515)

    Results from OddPub: Thank you for sharing your code.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There are several limitations of our study which primarily reflect the inherent limitations of our genomic surveillance program. A degree of selection bias exists within our dataset given that specimens were screened by cycle threshold value and were submitted by a selected group of clinical and commercial labs that cannot perfectly represent all COVID-19 cases in NY. We were unable to assess the demographic and clinical representativeness of our dataset because these data were not available to us for many specimens. Additionally, the number of specimens sequenced varied over the space and time of the study period, which created small sample sizes within many ZCTA-months. This limitation extended to the multinomial scan statistic, which was run with estimated values for COVID-19 cases attributable to B.1.1.7 and B.1.526, giving all ZCTAs with samples equal weight. However, the spatial scan assesses data according to their proximity to each other. In this context, ZCTAs are analyzed together rather than individually, which has the potential to reduce bias. Another consequence of our limited sampling was that our data exhibited zero samples from many ZCTAs for each month. We addressed this by using IDW interpolation of the proportion of B.1.1.7 and B.1.526 sequenced samples at the ZCTA-month level to visualize general patterns of variant proportions over geography. Phylogeographic analyses were hampered by similar limitations: uneven sampling among regions and the lack of globa...

    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 10.1101/2021.09.14.21262977v1 on medRxiv