Few studies have proposed methods for sample size determination and specification of passing criterion (e.g., number needed to pass from a given size panel) for respirator fit-tests. One approach is to account for between- and within- subject variability, and thus take full advantage of the multiple donning measurements within subject, using a random effects model. The corresponding sample size calculation, however, may be difficult to implement in practice, as it depends on the model-specific and test panel-specific variance estimates, and thus does not yield a single sample size or specific cutoff for number needed to pass. A simple binomial approach is therefore proposed to simultaneously determine both the required sample size and the optimal cutoff for the number of subjects needed to achieve a passing result. The method essentially conducts a global search of the type I and type II errors under different null and alternative hypotheses, across the range of possible sample sizes, to find the lowest sample size which yields at least one cutoff satisfying, or approximately satisfying all pre-determined limits for the different error rates. Benchmark testing of 98 respirators (conducted by the National Institute for Occupational Safety and Health) is used to illustrate the binomial approach and show how sample size estimates from the random effects model can vary substantially depending on estimated variance components. For the binomial approach, probability calculations show that a sample size of 35 to 40 yields acceptable error rates under different null and alternative hypotheses. For the random effects model, the required sample sizes are generally smaller, but can vary substantially based on the estimate variance components. Overall, despite some limitations, the binomial approach represents a highly practical approach with reasonable statistical properties.

Previous studies have shown a sampling probe bias for measuring fit factors (FFs) in respirator facepieces. This study was conducted to evaluate three sampling probes for fit testing NIOSH-certified N95 filtering facepiece respirators (FFRs). Two phases of fit test experiments were conducted incorporating 'side-by-side' probe mounting: (i) flush probe versus deep probe and (ii) flush probe versus disc probe. Seven test subjects in Phase 1 and six subjects in Phase 2 were fit tested with one to three N95 FFR models for a total of 10 subject/FFR model combinations for each phase. For each experimental condition, induced faceseal leakage (IFSL) through an induced leak was measured using a PORTACOUNT® Plus model 8020A Respirator Fit Tester with a model 8095 N95-Companion™ accessory. For Phase 1, the mean IFSL of all flush probe measurements (3.6%) was significantly greater than (P < 0.05) the mean IFSL of all deep probe measurements (3.3%). For Phase 2, the mean IFSL of all flush probe measurements (8.5%) was not significantly greater than (P > 0.05) the mean IFSL of all disc probe measurements (8.3%). Results indicate that some leak site and subject/FFR model/leak site combination comparisons (flush probe versus deep probe or flush probe versus disc probe) were statistically different (P < 0.05). The overall mean IFSL for subject/FFR model/leak site combinations differed by 14 and 4% for the flush probe versus deep probe and the flush probe versus disc probe, respectively; however, from a practical standpoint, there is little difference between the flush probe tests compared with the deep probe or disc probe tests. Overall, IFSL measured using the flush probe is higher (resulting in a more conservative measure of faceseal leakage) compared with either the deep probe or disc probe. The more conservative results obtained using the flush probe provide support for its common usage for fit testing cup-shaped FFRs in the USA and potential use for fit testing FFRs in Europe.

A previous study used a PortaCount Plus to measure the ratio of particle concentrations outside (Cout) to inside (Cin) of filtering facepiece respirators (FFRs) worn by test subjects and calculated the total inward leakage (TIL) (Cin/Cout) to evaluate the reproducibility of the TIL test method between two different National Institute for Occupational Safety and Health laboratories (Laboratories 1 and 2) at the Pittsburgh Campus. The purpose of this study is to utilize the originally obtained PortaCount Cout/Cin ratio as a measure of protection factor (PF) and evaluate the influence of particle distribution and filter efficiency. PFs were obtained for five N95 model FFRs worn by 35 subjects for three donnings (5 models × 35 subjects × 3 donnings) for a total of 525 tests in each laboratory. The geometric mean of PFs, geometric standard deviation (GSD), and the 5th percentile values for the five N95 FFR models were calculated for the two laboratories. Filter efficiency was obtained by measuring the penetration for four models (A, B, C, and D) against Laboratory 2 aerosol using two condensation particle counters. Particle size distribution, measured using a Scanning Mobility Particle Sizer, showed a mean count median diameter (CMD) of 82 nm in Laboratory 1 and 131 nm in Laboratory 2. The smaller CMD showed relatively higher concentration of nanoparticles in Laboratory 1 than in Laboratory 2. Results showed that the PFs and 5th percentile values for two models (B and E) were larger than other three models (A, C, and D) in both laboratories. The PFs and 5th percentile values of models B and E in Laboratory 1 with a count median diameter (CMD) of 82 nm were smaller than in Laboratory 2 with a CMD of 131 nm, indicating an association between particle size distribution and PF. The three lower efficiency models (A, C, and D) showed lower PF values than the higher efficiency model B showing the influence of filter efficiency on PF value. Overall, the data show that particle size distribution and filter efficiency influence the PFs and 5th percentile values. The PFs and 5th percentile values decreased with increasing nanoparticle concentration (from CMD of 131 to 82 nm) indicating lower PFs for aerosol distribution within nanoparticle size range (<100 nm). Further studies on the relationship between particle size distribution and PF are needed to better understand the respiratory protection against nanoparticles.

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