College of Engineering
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The College of Engineering at Montana State University will serve the State of Montana and the nation by fostering lifelong learning, integrating learning and discovery, developing and sharing technical expertise, and empowering students to be tomorrow's leaders.
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Item Guidelines for the statistical analysis of a collaborative study of a laboratory method for testing disinfectant product performance(2013-09) Hamilton, Martin A.; Hamilton, G. C.; Goeres, Darla M.; Parker, Albert E.This paper presents statistical techniques suitable for analyzing a collaborative study (multilaboratory study or ring trial) of a laboratory disinfectant product performance test (DPPT) method. Emphasis is on the assessment of the repeatability, reproducibility, resemblance, and responsiveness of the DPPT method. The suggested statistical techniques are easily modified for application to a single laboratory study. The presentation includes descriptions of the plots and tables that should be constructed during initial examination of the data, including a discussion of outliers and QA checks. The statistical recommendations deal with evaluations of prevailing types of DPPTs, including both quantitative and semiquantitative tests. The presentation emphasizes tests in which the disinfectant treatment is applied to surface-associated microbes and the outcome is a viable cell count; however, the statistical guidelines are appropriate for suspension tests and other test systems. The recommendations also are suitable for disinfectant tests using any microbe (vegetative bacteria, virus, spores, etc.) or any disinfectant treatment. The descriptions of the statistical techniques include either examples of calculations based on published data or citations to published calculations. Computer code is provided in an appendix.Item A statistical model for assessing performance standards for quantitative and semi-quantitative disinfectant test methods(2014-01) Parker, Albert E.; Hamilton, Martin A.; Tomasino, S. F.A performance standard for a disinfectant test method can be evaluated by quantifying the (Type I) pass-error rate for ineffective products and the (Type II) fail-error rate for highly effective products. This paper shows how to calculate these error rates for test methods where the log reduction in a microbial population is used as a measure of antimicrobial efficacy. The calculations can be used to assess performance standards that may require multiple tests of multiple microbes at multiple laboratories. Notably, the error rates account for among-laboratory variance of the log reductions estimated from a multilaboratory data set and the correlation among tests of different microbes conducted in the same laboratory. Performance standards that require that a disinfectant product pass all tests or multiple tests on average, are considered. The proposed statistical methodology is flexible and allows for a different acceptable outcome for each microbe tested, since, for example, variability may be different for different microbes. The approach can also be applied to semiquantitative methods for which product efficacy is reported as the number of positive carriers out of a treated set and the density of the microbes on control carriers is quantified, thereby allowing a log reduction to be calculated. Therefore, using the approach described in this paper, the error rates can also be calculated for semiquantitative method performance standards specified solely in terms of the maximum allowable number of positive carriers per test. The calculations are demonstrated in a case study of the current performance standard for the semiquantitative AOAC Use-Dilution Methods for Pseudomonas aeruginosa (964.02) and Staphylococcus aureus (955.15), which allow up to one positive carrier out of a set of 60 inoculated and treated carriers in each test. A simulation study was also conducted to verify the validity of the model's assumptions and accuracy. Our approach, easily implemented using the computer code provided, offers a quantitative decision-making tool for assessing a performance standard for any disinfectant test method for which log reductions can be calculated.Item Use of statistical modeling to reassess the performance standard for the AOAC use-dilution methods (955.15 and 964.02)(2014-06) Tomasino, S. F.; Parker, Albert E.; Hamilton, Martin A.The AOAC Use-dilution methods (UDM) 955.15 (Staphylococcus aureus) and 964.02 (Pseudomonas aeruginosa) are laboratory methods used to substantiate antimicrobial efficacy claims for liquid disinfectants on inanimate surfaces. The UDM is accepted by the U.S. Environmental Protection Agency for the purpose of product registration. To attain a hospital-level claim, testing against S. aureus and P. aeruginosa is required, and the product must pass against both microbes. Currently, the UDM's performance standard for a single 60-carrier test is the same for both microbes, and allows up to one positive carrier for the product to be considered as a pass. In this paper, the performance standards for these methods are reassessed using data from a 2009 five-laboratory collaborative study and a recently published statistical model. The reassessment focuses on the pass-error rate for ineffective products and the fail-error rate for highly effective products. The calculations indicate that the pass-error rate is between 9 and 24% and the fail-error rate between 18 and 23% when the current performance standard is used for a single test. For product registration, a smaller pass-error rate (1%) historically has been maintained by requiring that a disinfectant pass three UDM tests for each of the two microbes; however, the calculations also indicate that the fail-error rate is between 42 and 45%. This large fail-error rate is a compelling reason to consider a new performance standard for the two UDM methods, 955.15 (S. aureus) and 964.02 (P. aeruginosa). One alternative performance standard allows no more than six positive carriers out of 60 as a pass when using P. aeruginosa and no more than three positive carriers out of 60 when using S. aureus. In addition, the new performance standard requires that three UDM tests be performed with each of the two microbes, and the disinfectant must pass all six tests to be considered efficacious. The statistical calculations for this alternative performance standard indicate that the pass-error rate is no more than 3%, while the fail-error rate is as small as 5%. Based on these error rate calculations, proposed revisions to the performance standards for AOAC Methods 955.15 and 964.02 are provided.