COVID-19: Mechanistic model calibration subject to active and varying non-pharmaceutical interventions

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Abstract

No abstract available

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  1. SciScore for 10.1101/2020.09.10.20191817: (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:
    The software has limitations, not the least being the considerable expertise needed to utilise it for this application which is significantly outside its designed purpose, and we are not advocating its use. Rather we are suggesting that the methodology embedded in the software with some further development of regressive capability could be developed into an effective software tool for epidemic study. This work is merely a demonstrator of the algorithmic steps involved. One aspect of the modelling software’s capability which was not used in this study is simulation of thermal runaway – the behaviour of a reacting system which accelerates exponentially. Batch chemical process development places strong emphasis on avoiding a violent thermal runaway, which a significant number of processes could potentially undergo unless properly designed. The methods for studying and the design procedures to negate the possibility of a thermal runaway are well established. There are many analogies in a thermal runaway scenario with the outbreak of an epidemic. For example, the explicit inclusion of the effective reproduction number in the model equation for infection reveals the stability characteristics of the system. Another feature which could be exploited is the modelling of reagent additions which is directly analogous to an influx of infected cases to a population. Such scenarios will be simulated and reported in a future publication. In conclusion, this study has attempted to assess the ...

    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.