Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study

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Abstract

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  1. SciScore for 10.1101/2020.02.21.20026328: (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:
    It is important to stress that this study is affected by the usual limitations pertaining to the data analysis of rapidly evolving infectious disease outbreaks. The statistical analysis could therefore include biases due to case ascertainment and non-homogenous sampling over time and by location. The level of ascertainment of mild cases remains unclear and could present a different epidemiological characterization. Although the estimates of the net reproduction number are not affected by an approximately constant underreporting rate of cases, they may suffer from time-varying reporting rates. It is also important to consider that the analyzed individual records were retrieved from different data sources and thus may be affected by geographical heterogeneities in sampling of cases with specific exposure (imported or locally acquired infections) and with available dates of symptom onset. However, we analyzed the completeness of individual records used in this study and compared them with official line lists for three locations in mainland China. We found that our data was of similar quality as the official complete line lists. Even in the presence of the above limitations, a timely updated patient line list like ours is critical to assess the epidemiology and transmission dynamics of an emerging pathogen, inform situational awareness, and optimize the responses to the outbreak. Since January 20, 2020, the National Health Commission of China incorporated COVID-19 as a notifiable...

    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.