Spatial variability in reproduction number and doubling time across two waves of the COVID-19 pandemic in South Korea, February to July, 2020

This article has been Reviewed by the following groups

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Abstract

No abstract available

Article activity feed

  1. SciScore for 10.1101/2020.07.21.20158923: (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
    Analytical estimates of Rt were obtained within a Bayesian framework using EpiEstim R package in R language version 3.6.3 (R Foundation for Statistical Computing, Vienna, Austria) (Cori et al., 2013).
    EpiEstim
    suggested: (EpiEstim, RRID:SCR_018538)

    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:
    Our study is not exempt of limitations including the lack of dates of symptoms onset for all of the cases, relying on a statistical reconstruction of the epidemic curve by dates of symptoms onset as in a previous study (Shim et al., 2020a). Overall, using most up-to-date epidemiological data from South Korea, our study highlights the effectiveness of strong control interventions in South Korea and emphasizes the need to maintain firm social distancing and contact tracing efforts to mitigate the risk of additional waves of the disease.

    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

    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.