Using Novel, Agent-Based Periodic Mobility Model with Super Spreaders to Analyze Vaccination Strategies for COVID-19

  1. Mathew Jacob
  2. Eva Xueyao Guo

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Abstract

The authors have withdrawn this manuscript because there have been a number of mutations of COVID-19, since the manuscript was posted, as well as changes in virus behavior, such as increased transmissibility. As a result, both the vaccination strategies and parameters used during the simulation are less applicable to the current situation, and thus the results from the simulations may be incorrect for the current situation. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

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  1. ScreenIT

    SciScore for 10.1101/2021.08.09.21261809: (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:
    For COVID-19, this is an important limitation because variants have been shown to exhibit properties such as being more transmissible and/or more deadly. Additionally, viruses like the Delta variant of COVID-19 seems to be just as transmissible from vaccinated people [10], which could potentially impact the results of this study. The second main assumption that this study makes is that vaccinated people can never get infected with the disease, not transmit the disease, and are instantly protected after the shot. While vaccines like Moderna and Pfizer-BioNTech mRNA vaccines work remarkably well, with the BNT162b2 mRNA vaccine of Pfizer and BioNTech having a 95% protection [11], there are documented cases of breakthrough infections, which are only increasing with the new Delta variant [12]. However, because of breakthrough infections’ rarity, it is unlikely they would have impacted the ICU hospitalizations and deaths greatly, leading the results found in this study to continue to be valid. In future studies, it would be beneficial to account for extraneous variables, such as the impact of variants and vaccine efficacy.

    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.

  2. Version published to 10.1101/2021.08.09.21261809 on medRxiv