Experimental Design for a Sponge-Wipe Study to Relate the Recovery Efficiency and False Negative Rate to the Concentration of a Bacillus anthracis Surrogate for Six Surface Materials

Piepel, Gregory F. ; Amidan, Brett G. ; Krauter, Paula ; Einfeld, Wayne

关键词: BACILLUS;    CERAMICS;    CLEARANCE;    CONTAMINATION;    DEPOSITION;    DESIGN;    EFFICIENCY;    LEATHER;    PERFORMANCE;    PROCESSING;    SAMPLING;    SANDIA NATIONAL LABORATORIES;    TESTING;    WOOD Anthrax;    Experimental design;    False negative rate;    Recovery efficiency;    Surface materials;   

DOI  :  10.2172/1019212
RP-ID  :  PNNL-20060 Rev. 1
PID  :  OSTI ID: 1019212
Others  :  Other: 400904120
Others  :  TRN: US201115%%37

学科分类：燃料技术

美国|英语

来源: SciTech Connect

【 摘 要 】

Two concerns were raised by the Government Accountability Office following the 2001 building contaminations via letters containing Bacillus anthracis (BA). These included the: 1) lack of validated sampling methods, and 2) need to use statistical sampling to quantify the confidence of no contamination when all samples have negative results. Critical to addressing these concerns is quantifying the false negative rate (FNR). The FNR may depend on the 1) method of contaminant deposition, 2) surface concentration of the contaminant, 3) surface material being sampled, 4) sample collection method, 5) sample storage/transportation conditions, 6) sample processing method, and 7) sample analytical method. A review of the literature found 17 laboratory studies that focused on swab, wipe, or vacuum samples collected from a variety of surface materials contaminated by BA or a surrogate, and used culture methods to determine the surface contaminant concentration. These studies quantified performance of the sampling and analysis methods in terms of recovery efficiency (RE) and not FNR (which left a major gap in available information). Quantifying the FNR under a variety of conditions is a key aspect of validating sample and analysis methods, and also for calculating the confidence in characterization or clearance decisions based on a statistical sampling plan. A laboratory study was planned to partially fill the gap in FNR results. This report documents the experimental design developed by Pacific Northwest National Laboratory and Sandia National Laboratories (SNL) for a sponge-wipe method. The testing was performed by SNL and is now completed. The study investigated the effects on key response variables from six surface materials contaminated with eight surface concentrations of a BA surrogate (Bacillus atrophaeus). The key response variables include measures of the contamination on test coupons of surface materials tested, contamination recovered from coupons by sponge-wipe samples, RE, and FNR. The experimental design involves 16 test runs, performed in two blocks of eight runs. Three surface materials (stainless steel, vinyl tile, and ceramic tile) were tested in the first block, while three other surface materials (plastic, painted wood paneling, and faux leather) were tested in the second block. The eight surface concentrations of the surrogate were randomly assigned to test runs within each block. Some of the concentrations were very low and presented challenges for deposition, sampling, and analysis. However, such tests are needed to investigate RE and FNR over the full range of concentrations of interest. In each run, there were 10 test coupons of each of the three surface materials. A positive control sample was generated at the same time as each test sample. The positive control results will be used to 1) calculate RE values for the wipe sampling and analysis method, and 2) fit RE- and FNR-concentration equations, for each of the six surface materials. Data analyses will support 1) estimating the FNR for each combination of contaminant concentration and surface material, 2) estimating the surface concentrations and their uncertainties of the contaminant for each combination of concentration and surface material, 3) estimating RE (%) and their uncertainties for each combination of contaminant concentration and surface material, 4) fitting FNR-concentration and RE-concentration equations for each of the six surface materials, 5) assessing goodness-of-fit of the equations, and 6) quantifying the uncertainty in FNR and RE predictions made with the fitted equations.