Rapid incidence estimation from SARS-CoV-2 genomes reveals decreased case detection in Europe during summer 2020

  1. Maureen Rebecca Smith
  2. Maria Trofimova
  3. Ariane Weber
  4. Yannick Duport
  5. Denise Kühnert
  6. Max von Kleist

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Abstract

By October 2021, 230 million SARS-CoV-2 diagnoses have been reported. Yet, a considerable proportion of cases remains undetected. Here, we propose GInPipe, a method that rapidly reconstructs SARS-CoV-2 incidence profiles solely from publicly available, time-stamped viral genomes. We validate GInPipe against simulated outbreaks and elaborate phylodynamic analyses. Using available sequence data, we reconstruct incidence histories for Denmark, Scotland, Switzerland, and Victoria (Australia) and demonstrate, how to use the method to investigate the effects of changing testing policies on case ascertainment. Specifically, we find that under-reporting was highest during summer 2020 in Europe, coinciding with more liberal testing policies at times of low testing capacities. Due to the increased use of real-time sequencing, it is envisaged that GInPipe can complement established surveillance tools to monitor the SARS-CoV-2 pandemic. In post-pandemic times, when diagnostic efforts are decreasing, GInPipe may facilitate the detection of hidden infection dynamics.

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  1. Version published to 10.1038/s41467-021-26267-y
  2. Version published to 10.21203/rs.3.rs-558667/v1 on Research Square
  3. ScreenIT

    SciScore for 10.1101/2021.05.14.21257234: (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
    Implementation and availability: All methods were implemented in Python version 3.9 and R version 4.0.
    Python
    suggested: (IPython, RRID:SCR_001658)
    A fully automated workflow has been generated using Snakemake [26] and is available from https://github.com/KleistLab/GInPipe.
    Snakemake
    suggested: (Snakemake, RRID:SCR_003475)
    Phylodynamic analyses: Phylodynamic analyses were performed on subsampled sets of the data described above (Data and data pre-processing) using a birth-death-sampling process as implemented in the BDSKY [53] model in BEAST2 [5].
    BEAST2
    suggested: (BEAST2, RRID:SCR_017307)
    Retained sequences were aligned to the reference genome (Genbank-ID MN908947.3 [3]) in MAFFT [22] using the –keeplength option and problematic sites were masked by replacing the them with ‘N’ in the alignment [11].
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Log files are assessed using Tracer and TreeAnnotator was used to summarize the posterior sample of phylogenetic trees to a maximum clade credibility tree using median node heights.
    Tracer
    suggested: (Tracer, RRID:SCR_019121)
    Relative case detection rate: We used GInPipe to detect changes in SARS-CoV-2 case detection.
    GInPipe
    suggested: None

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

    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.

    About SciScore

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  4. Version published to 10.1101/2021.05.14.21257234v1 on medRxiv