How Efficient Can Non-Professional Masks Suppress COVID-19 Pandemic?
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Abstract
The coronavirus disease 2019 (COVID-19) pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which can be transmitted via respiratory secretions. Since there are currently no specific therapeutics or vaccines available against the SARS-CoV-2, the commen non-pharmaceutical interventions (NPIs) are still the main measures to curb the COVID-19 epidemic. Face mask wearing is one important measure to suppress the pandemic. In order to know how efficient is face mask wearing in reducing the pandemic even with low efficiency non-professional face masks, we exploit physical abstraction to model the non-professional face masks made from cotton woven fabrics and characterize them by a parameter virus penetration rate (VPR) γ . Monte Carlo simulations exhibit that the effective reproduction number R of COVID-19 or similar pandemics can be approximately reduced by factor γ 4 with respect to the basic reproduction number R 0 , if the face masks with 70% < γ < 90% are universally applied for the entire network. Furthermore, thought experiments and practical exploitation examples in country-level and city-level are enumerated and discussed to support our discovery in this study and indicate that the outbreak of a COVID-19 like pandemic can be even suppressed by the low efficiency non-professional face masks.
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SciScore for 10.1101/2020.05.31.20117986: (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 10.1101/2020.05.31.20117986: (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.
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