Now-casting the COVID-19 epidemic: The use case of Japan, March 2020

  1. Stephan Glöckner
  2. Gérard Krause
  3. Michael Höhle

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Abstract

Background

Reporting delays in disease surveillance impair the ability to assess the current dynamic of an epidemic. In continuously updated epidemic curves, case numbers for the most recent epidemic week or day usually appear to be lower than the previous, suggesting a decline of the epidemic. In reality, the epidemic curve may still be on the rise, because reporting delay prevents the most recent cases to appear in the case count. In context of the COVID-19 epidemic and for countries planning large international gatherings, such as the Summer Olympic Games in Japan 2020, the ability to assess the actual stage of an epidemic is of outmost importance.

Methods

We applied now-casting onto COVID-19 data provided by the nCoV-2019 Data Working Group to evaluate the true count of cases, by taking into account reporting delays occurring between date of symptom onset and date of confirmation.

Findings

We calculated a decrease of reporting delay, from a median delay of ten days in calendar week four 2020 to six days in calendar week eight, resulting in an overall mean of 4.3 days. The confidence intervals of the now-casting indicated an increase of cases in the last reporting days, while case country in that same time period suggested a decline.

Interpretation

As a specific use case this tool may be of particular value for the challenging risk assessment and risk communication in the context of the Summer Olympic Games in Japan 2020 and similar situations elsewhere.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.18.20037473: (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
    We developed this approach within R14 using the open-source R package surveillance15 and developed a Shiny application16,17, allowing users to perform now-casting without need for sophisticated programming skills and made it available at: https://helmholtz-epid.shinyapps.io/nowcasting_dashboard/.
    Shiny
    suggested: (Shiny, RRID:SCR_001626)

    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: 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.

    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.

  2. ScreenIT

    SciScore for 10.1101/2020.03.18.20037473: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We developed this approach within R14 using the open-source R package surveillance15 and developed a Shiny application16,17 , allowing users to perform now-casting without need for sophisticated programming skills and made it available at: https://helmholtz-epid.shinyapps.io/nowcasting_dashboard/ .
    Shiny
    suggested: (Shiny, SCR_001626)

    Results from Barzooka: We also found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from OddPub: Thank you for sharing your code.

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, please follow this link.

  3. Version published to 10.1101/2020.03.18.20037473 on medRxiv