Transmission onset distribution of COVID-19

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

No abstract available

Article activity feed

  1. SciScore for 10.1101/2020.05.13.20101246: (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

    No key resources detected.


    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:
    This study has several limitations. First, the dates of symptom onset and contact time were identified from epidemiological investigation and it could be false due to recall bias. Second, we only collected data from definite infector-infectee pairs with defined contact times. Hence, our estimation of transmission onset distribution is the upper bound of the true value. Third, considering the substantial proportion of pre-symptomatic transmission, it is possible that one infectee had multiple infectors, and so-called effective contacts could not be identified. Fourth, we excluded clustered data to promote the accuracy of causal relationships. The transmission behavior of SARS-CoV-2 might have different characteristics within unique clusters, but this could not be measured in this study. Fifth, we might not catch the late-onset transmission cases, considering the pre-emptive screening and isolation measures implemented in South Korea. This study provides an important message in terms of public health practice. It indicates that the usual preventive measure of isolating people when they become symptomatic, might be too late to prevent SARS-CoV-2 transmission.

    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.