Mechanistic investigation of fitted mask source control efficacy for sub-micrometer aerosols
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other mucosal respiratory viruses spread through both respiratory droplets and aerosols. The apparent filtration efficiency of surgical, KN95, and N95 masks, donned on a physiologically realistic headform, is evaluated as source control for aerosol particle sizes in the 0.2 to 1 μm range. Material filtration efficiency is also evaluated to establish baseline values in the absence of leakages associated with mask fit. Barrier methods with higher stated filtration efficiency demonstrated greater filtration of sub-micrometer particles. However, the apparent filtration efficiency (ηAFE) was equivalent across the entire spectrum of sub-micrometer particle sizes tested, in contrast to the material filtration efficiency that was sensitive to particle size for the same aerosols. Aided by flow visualization, the analysis of the results shows that the apparent mask filtration efficiency is driven by leakages at the mask-skin interface. The conclusion was reinforced by a comparative analysis with relevant data available from other studies. The obtained statistics provide a range of outward filtration efficiencies that can be expected for an average user who follows manufacturer donning instructions, with 6%≲ηAFE≲40%, 24%≲ηAFE≲54%, and 52%≲ηAFE≲82% expected for a certified surgical, KN95, and N95 masks, respectively. The analysis also highlights important methodological considerations for future studies.Copyright © 2025 American Association for Aerosol Research
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".