COVID-19 in the California State Prison System: an Observational Study of Decarceration, Ongoing Risks, and Risk Factors
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SciScore for 10.1101/2021.03.04.21252942: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: IRB Approval: Stanford’s institutional review board granted approval (IRB-55835). Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. 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 access to person-level, daily data from a large prison system with high rates of testing created analytical opportunities that recent studies of …
SciScore for 10.1101/2021.03.04.21252942: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: IRB Approval: Stanford’s institutional review board granted approval (IRB-55835). Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. 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 access to person-level, daily data from a large prison system with high rates of testing created analytical opportunities that recent studies of Covid-19 in incarcerated populations have not had, including minimizing biases from selection into testing, However, our study also had limitations. First, we could not identify networks of specific contacts, a limitation that is likely to have mattered most to our estimates of the effect of labor participation. Second, we used room occupancy to indicate in-room contacts because density measures (e.g., residents per square foot) were not available. The most plausible effect of misclassifying room exposures would be to bias to the null our estimates of the effect of living in higher occupancy rooms. Third, we lacked information on some potential exposures, such as contacts with staff and during meals in common areas. Finally, although CDCR undertook extensive testing, not all residents were tested and test frequency varied across institutions. If residents of dormitories or of rooms with labor participation were tested relatively frequently, or testing there more precisely targeted infected residents, our estimates of these factors on infection risk may be biased upward. Prisons remain particularly dangerous settings for Covid-19-related morbidity and mortality. Our study shows that thousands of vulnerable incarcerated people continue to be housed in settings where their risk of Covid-19 infection is high. Protective measures such...
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.
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