The COVID-19 Suffolk Events Toolkit (C-SET): A structured approach to conducting COVID-secure events

  1. Avirup Chowdhury
  2. Terezija Zermanos
  3. Xinming Yu
  4. Padmanabhan Badrinath

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Abstract

Objectives

To develop a toolkit to provide a structured framework for assessing whether large events are COVID-secure.

Study design

Cross-sectional reporting on the development of the COVID-19 Suffolk Events Toolkit (C-SET).

Methods

The toolkit was developed through an iterative process of writing, discussion, and modification, drawing upon national UK guidance. Pilot cases and a contemporaneous consultation with experts were also undertaken, and C-SET was revised in line with the findings.

Results

C-SET offers a robust, structured approach to identifying areas of concern and potential mitigations, and collates and synthesises current national UK guidance. A flexible, modular design allows it to provide high-level input across all types of event, and allow modification to suit the needs of individual organisations. It is applicable to a variety of users, including event organisers in need of a structure, or bodies whose role is to appraise such events. It provides a semi-quantitative summary output, and in conjunction with the detailed links to guidance in the framework, allows development of clear, actionable recommendations to tangibly improve the quality of events.

Conclusions

A necessary trade-off exists between COVID-related health risks and wider risks due to economic downturn, and facilitating large events in a way that minimises COVID transmission risk may offer a way to balance these competing priorities. C-SET was developed to provide a structured approach to identifying areas of improvement across key risk domains, and suggests potential mitigations that are underpinned by national UK guidance. Use of this toolkit may aid event organisers in developing COVID-secure events, and aid regulatory bodies in suggesting actionable recommendations through generation of a summary report of areas of concern.

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  1. ScreenIT

    SciScore for 10.1101/2020.10.23.20218412: (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

    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:
    Limitations of the study: In order to remain user-friendly but comprehensive, some of the guidance is generic in nature: depending upon the specific scope and context of the event, certain sections may not be relevant (e.g. if there is no overnight accommodation being provided as part of the event). Furthermore, there may be subtle differences between modifications required in specific circumstances; this toolkit tends to utilise high-level groupings, with specific additional guidance provided in the corresponding section of the framework. For example, while camp-sites may have different requirements to dormitories, common themes are listed in C-SET, and this is advised in framework. Suggested mitigations outlined within C-SET are not exhaustive. Other mitigations may be appropriate, according to the specifics of the event; however, it is anticipated that those using this toolkit will have subject expertise sufficient to make these decisions. In addition, this toolkit does not account for activities associated with preparation for an event, such as rehearsals ahead of performing arts events. These considerations, while important, are likely to be very different from one event to another, and capturing the full breadth of these would negatively impact usability. However, the principles outlined in C-SET may be used to inform future work in this area. National guidance is changing in line with the evolving COVID-19 situation. Whilst several principles are likely to apply throug...

    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. Version published to 10.1101/2020.10.23.20218412 on medRxiv