Measuring the fitted filtration efficiency of cloth masks, medical masks and respirators
Bibliographic record
Abstract
IMPORTANCE: Masks reduce transmission of SARS-CoV2 and other respiratory pathogens. Comparative studies of the fitted filtration efficiency of different types of masks are scarce. OBJECTIVE: To describe the fitted filtration efficiency against small aerosols (0.02-1 µm) of medical and non-medical masks and respirators when worn, and how this is affected by user modifications (hacks) and by overmasking with a cloth mask. DESIGN: We tested a 2-layer woven-cotton cloth mask of a consensus design, ASTM-certified level 1 and level 3 masks, a non-certified mask, KF94s, KN95s, an N95 and a CaN99. SETTING: Closed rooms with ambient particles supplemented by salt particles. PARTICIPANTS: 12 total participants; 21-55 years, 68% female, 77% white, NIOSH 1-10. MAIN OUTCOME AND MEASURE: Using standard methods and a PortaCount 8038, we counted 0.02-1 µm particles inside and outside masks and respirators, expressing results as the percentage filtered by each mask. We also studied level 1 and level 3 masks with earguards, scrub caps, the knot-and-tuck method, and the effects of braces or overmasking with a cloth mask. RESULTS: Filtration efficiency for the cloth mask was 47-55%, for level 1 masks 52-60%, for level 3 masks 60-77%. A non-certified KN95 look-alike, two KF94s, and three KN95s filtered 57-77%, and the N95 and CaN99 97-98% without fit testing. External braces and overmasking with a well-fitting cloth mask increased filtration, but earguards, scrub caps, and the knot-and-tuck method did not. LIMITATIONS: Limited number of masks of each type sampled; no adjustment for multiple comparisons. CONCLUSIONS AND RELEVANCE: Well-fitting 2-layer cotton masks filter in the same range as level 1 masks when worn: around 50%. Level 3 masks and KN95s/KF94s filter around 70%. Over a level 1 mask, external braces or overmasking with a cloth-mask-on-ties produced filtration around 90%. Only N95s and CaN99s, both of which have overhead elastic, performed close to the occupational health and safety standards for fit tested PPE (>99%), filtering at 97-99% when worn, without formal fit testing. These findings inform public health messaging about relative protection from aerosols afforded by different mask types and explain the effectiveness of cloth masks observed in numerous epidemiologic studies conducted in the first year of the pandemic. A plain language summary of these findings is available at https://maskevidence.org/masks-compared.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".