Masking significantly reduces, but does not eliminate COVID-19 infection in a spatial agent-based simulation of a University dormitory floor
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Abstract
COVID-ADAPT is a stochastic, discrete-space, agent-based simulation model of airborne infection and public health interventions, capable of modeling SARS-CoV-2 transmission. Using a map of a real university dormitory floor, the model simulates agents moving about and potentially infecting each other. Health interventions tested are vaccination and masking, including whether the solitary initial infectious agent was masked. Universal masking with N95 masks and 100% vaccination of susceptible people resulted in significantly lower prevalence after 3 weeks compared to all other scenarios, but still led to a substantial number of infections. Increased vaccination levels from 52% to 100% by itself did not result in a significant difference in prevalence due to symptomatic and asymptomatic breakthrough infections. These results suggest that vaccination alone is insufficient to stem outbreaks, and the best way to reduce COVID-19 infections is to ensure that all infectious people are masked. However, because asymptomatic infections are common, the only way to ensure this is universal masking, which also reduces prevalence by protecting susceptible individuals from infection. Universal masking is the best way forward, especially under threat of the Delta variant, to keep facilities open and safe for occupants, while minimizing the number of infections.
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SciScore for 10.1101/2021.09.13.21263458: (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:Like any model that seeks to simulate aspects of reality while remaining tractably simplified, COVID-ADAPT has limitations. Chief among these is that the behavior of infected agents does not change, such as with isolation or even reduced movement if the individual were symptomatic. However, these scenarios are modeling a dorm floor in …
SciScore for 10.1101/2021.09.13.21263458: (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:Like any model that seeks to simulate aspects of reality while remaining tractably simplified, COVID-ADAPT has limitations. Chief among these is that the behavior of infected agents does not change, such as with isolation or even reduced movement if the individual were symptomatic. However, these scenarios are modeling a dorm floor in which, even if an individual is isolating in their room, might still use restrooms and common hallways. In previous terms, students testing positive at EWU were removed to quarantine dorms to reduce this sort of incidental exposure to others. Undoubtedly, though, this only concerned students tested, whether by choice or due to contact tracing turning up exposure. Therefore, asymptomatically infected students who were not aware of their exposure, occurring perhaps in a semi-anonymous public space, such as the grocery store or the cafeteria, where contact tracing is unlikely, would still go about their business on their dorm floors, potentially infecting others. In this way, the asymptomatic possibility provides reasoning for this scenario. Additionally, COVID-ADAPT as a model is intended to provide data on whether specific interventions reduce spread, and this is currently best modeled with a contained population. For this reason, too, death, hospitalization, and other causes of removal from the floor are not modeled. Future iterations of the model may include more complex movement behaviors, including movement to other floors and eventually othe...
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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