Outbreaks of COVID-19 variants in US prisons: a mathematical modelling analysis of vaccination and reopening policies

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Abstract

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  1. SciScore for 10.1101/2021.05.03.21256525: (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:
    Our study has several limitations, First, our results may not be fully generalizable to other carceral settings. The impacts of infection introduction on incarcerated populations depend in part on how likely prisons are to detect outbreaks and take measures to isolate and quarantine. Our results are based on modeling of widespread testing as practiced in California’s prisons during 2020-21. However, in settings where screening and testing are less intensive, the risk and size of outbreaks are likely to be larger than our estimates. Although we modeled a range of prison types, incarcerated populations, and levels of prior immunity, outcomes in individual prisons could differ if their housing configurations or demographics diverge substantially from those modeled. Second, while we considered variant scenarios that broadly represent variants like B.1.1.7 along with scenarios considering introduction of wild type variants, other variants are currently circulating globally, and new variants are emerging even as the scientific community works to keep pace in characterizing them epidemiologically (12,15). Some variants may be able to completely evade natural immunity from prior wild type infection; although we did not model these explicitly, we did model equivalent scenarios with 0% baseline immunity. However, variants that are simultaneously able to avoid vaccine-induced immunity and much more likely to cause severe outcomes, though not yet detected, would require further evaluatio...

    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

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