The Impact of COVID-19 Vaccination on the Italian Healthcare System: A Scenario Analysis

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Abstract

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  1. SciScore for 10.1101/2021.06.08.21258561: (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:
    This study has some limitations that also open opportunities for future research. First, the model did not include any epidemiological simulations and herd immunity was not considered in the analysis. Consequently, the indirect protection caused by the increasing size of the vaccinated population is a factor that has the potential to increase the effects of immunisation more quickly than is forecast in this model. Second, several assumptions were made based on the data and the knowledge accumulated in 2020. The data informing our model is being constantly updated and therefore, some of the assumptions used may require an update. However, the model will be constantly calibrated and updated with new data and therefore it represents a potential tool that policymakers may find useful in the control of the pandemic. Lastly, the efficacy shown by vaccines needs to be further demonstrated in the real world, in particular regarding the duration of the protection and whether vaccinated people can be infectious.

    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.

    Results from scite Reference Check: We found no unreliable references.


    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.