Statistical modeling of respirator penetration data.
Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, R01-OH-003570, 2003 Jan; :1-19
A normal random effects model for log-transformed respirator penetration P values was formulated, where P is the ratio of the contaminant concentration inside the respirator C1 to the ambient contaminant concentration outside the respirator C(o). The model accounts for within- and between-wearer variability in P. Thirty three published and unpublished studies were located which contained measurements for P from multiple respirator wearers, but only seven studies of negative-pressure air-purifying halfmask respirators (HMR's) and two studies of helmet- and-visor type powered air-purifying respirators (PAPR's) provided sufficient detail. In each study, the model for In P was fit by the method of maximum likelihood, which yielded estimates of the overall mean In P value ul, the within-wearer variance delta2omega , and the between-wearer variance delta2beta. In the seven HMR studies, the estimated between-wearer variance component contributed, respectively, 0%, 0%, 6.5%, 11 %, 23%, 46% and 51 % of the total variance. The findings indicate that for HMR use, the within-wearer variance tends to dominate the between-wearer variance. In the two PAPR studies, the between-wearer variance component contributed, respectively, 0% and 43% of the total variance. Criteria were specified for the assigned penetration factor APF(P) (the inverse of the assigned protection factor APF), namely, no more than 5% of wearers experience more than 5% of P values above the APF(P) value.
Statistical-analysis; Models; Respirators; Air-contamination; Respiration; Air-purification; Air-purifiers; Air-purifying-respirators; Personal-protective-equipment; Protective-equipment
Final Grant Report
NTIS Accession No.
Research Tools and Approaches: Control Technology and Personal Protective Equipment
National Institute for Occupational Safety and Health
University of California, Berkeley, California