Modeling COVID-19 Aerosol Transmission in Primary Schools
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Abstract
Schools must balance public health, education, and social risks associated with returning to in-person learning. These risks are compounded by the ongoing uncertainty about vaccine availability and uptake for children under 12 years of age. In this paper, we show how the risk of infections that result directly from in-class aerosol transmission within an elementary school population can be estimated in order to compare the effects of different countermeasures. We compare the effectiveness of these countermeasures in reducing transmission including required masking at three levels of mask effectiveness, improving room airflow exchange rates, weekly testing of the students, and lunch partitioning. Our results show that multiple layers of interventions are necessary to keep in-class infections relatively low. These results can inform school administrators about how these interventions can help manage COVID-19 spread within their own elementary school populations.
Article activity feed
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SciScore for 10.1101/2021.12.08.21267499: (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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.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…
SciScore for 10.1101/2021.12.08.21267499: (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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.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.
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