Investigating the first stage of the COVID-19 pandemic in Ukraine using epidemiological and genomic data

  1. Yuriy Gankin
  2. Alina Nemira
  3. Vladimir Koniukhovskii
  4. Gerardo Chowell
  5. Thomas A. Weppelmann
  6. Pavel Skums
  7. Alexander Kirpich

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Abstract

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  1. Version published to 10.1016/j.meegid.2021.105087
  2. ScreenIT

    SciScore for 10.1101/2021.03.05.21253014: (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
    The second analysis part was the phylodynamic analysis which was performed using BEAST v1.10.4 [50] for 60 Ukrainian sequences.
    BEAST
    suggested: (BEAST, RRID:SCR_010228)
    MCMC behaviour was satisfactory with reasonable effective sample sizes above 200 calculated by Tracer v1.10.4.
    Tracer
    suggested: (Tracer, RRID:SCR_019121)

    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:
    The findings from this paper are of course not without limitations. As one of the poorest countries in Europe (based on GDP per capita) much of the health care infrastructure in Ukraine lacks the resources of its neighbors [73]. Both availability of screening tests and the reporting of incidence data during the initial epidemic likely underestimated the burden of disease. Likewise, as the pandemic evolved, the scarcity of genetic sequencing limited the number of sequence comparison in the phylogenetic analysis. As such, the number of actual viral clusters remains unknown and should be interpreted as at least eight clusters. The findings however, do provide a clear indication of a local transmission within Ukraine and were useful to establish a timeline for viral introduction. In summary, this study was among the first to explore the characteristics of the initial pandemic as it spread to Ukraine and provided additional genomic analyses not previously published. Not only does the use of the local stochastic model support the efficacy of non-pharmacologic measures such as quarantine to reduce the spread of illness, it demonstrated that even small delays in implementation can have large effects on the number of future cases.

    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

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  3. Version published to 10.1101/2021.03.05.21253014 on medRxiv