Predicting Hospital Demand During the COVID-19 Outbreak in Bogotá, Colombia

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Abstract

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  1. SciScore for 10.1101/2020.04.14.20065466: (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:
    Other than the intrinsic limitations of SEIR models, this prediction model does not account for age and sex distribution of the population but we plan to introduce such differences in a future version of the model with an additional mixing including the contact matrices, as the recently national population census in Colombia is available. Also, we have fitted a a model with two interventions: a lockdown and mitigation measures, but this can be modified later in time. Neither we accounted for regional differences that in a tropical context relate to weather and climate, because there is no evidence, to date, that the novel coronavirus could or not spread in an homogeneous pattern under certain weather conditions. Finally, we provide a Shiny app available in https://claudia-rivera-rodriguez.shinyapps.io/s The original values in the app reproduce the results of this paper, but the parameters and starting values can be changed according to the users needs.

    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.
    • No funding statement was detected.
    • 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.