False-Negative Rate and Recovery Efficiency Performance of a Validated Sponge Wipe Sampling Method
Author(s) -
Paula Krauter,
Greg F. Piepel,
Raymond Boucher,
Matt Tezak,
Brett G. Amidan,
Wayne Einfeld
Publication year - 2011
Publication title -
applied and environmental microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.552
H-Index - 324
eISSN - 1070-6291
pISSN - 0099-2240
DOI - 10.1128/aem.07403-11
Subject(s) - spore , tile , surface roughness , sampling (signal processing) , detection limit , materials science , surface finish , composite material , analytical chemistry (journal) , biology , chemistry , chromatography , botany , optics , physics , detector
Recovery of spores from environmental surfaces varies due to sampling and analysis methods, spore size and characteristics, surface materials, and environmental conditions. Tests were performed to evaluate a new, validated sponge wipe method usingBacillus atrophaeus spores. Testing evaluated the effects of spore concentration and surface material on recovery efficiency (RE), false-negative rate (FNR), limit of detection (LOD), and their uncertainties. Ceramic tile and stainless steel had the highest mean RE values (48.9 and 48.1%, respectively). Faux leather, vinyl tile, and painted wood had mean RE values of 30.3, 25.6, and 25.5, respectively, while plastic had the lowest mean RE (9.8%). Results show roughly linear dependences of RE and FNR on surface roughness, with smoother surfaces resulting in higher mean REs and lower FNRs. REs were not influenced by the low spore concentrations tested (3.10 × 10−3 to 1.86 CFU/cm2 ). Stainless steel had the lowest mean FNR (0.123), and plastic had the highest mean FNR (0.479). The LOD90 (≥1 CFU detected 90% of the time) varied with surface material, from 0.015 CFU/cm2 on stainless steel up to 0.039 on plastic. It may be possible to improve sampling results by considering surface roughness in selecting sampling locations and interpreting spore recovery data. Further, FNR values (calculated as a function of concentration and surface material) can be used presampling to calculate the numbers of samples for statistical sampling plans with desired performance and postsampling to calculate the confidence in characterization and clearance decisions.
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