title: The impact of screening-test negative samples not enumerated by MPN.
abstract: In microbiological surveys, false negative results in detection tests precluding the enumeration by MPN may occur. The objective of this study was to illustrate the impact of screening test failure on the probability distribution of Salmonella concentrations in pork using a Bayesian method. A total of 276 swab samples in four slaughter steps (69 samples in each slaughter step: after dehairing, after singeing, after evisceration, and before chilling) were screened for Salmonella and enumerated by the MPN method. Salmonella contamination data were fitted to a lognormal distribution by using a Bayesian model that uses the number of positive tubes at each dilution in an MPN analysis to estimate the parameters of the concentration distribution. With Salmonella paired data, three data sets were used for each slaughter step: one that includes the positives in the screening test only, a second one that includes false negative results from the screening, and a third that considers the entire data set. The relative sensitivity of the screening test was also calculated assuming as gold standard samples with confirmed Salmonella. Salmonella was confirmed by a reference laboratory in 29 samples either by screening or MPN method. The relative sensitivity of the screening test was 69% (CI 95%: 52%-85%). The data set that included enumerations from screen-negative samples (false negative results) tended to have higher μ̂ and smaller σ̂ in comparison with the data set that discards false negative results, suggesting that the lack of sensitivity of the screening test affects the distribution that describes the contamination across the population. Numerous surveys on fitting distribution methods of microbial censored data have been published and discuss source of bias due to fitting method. Results of this survey contribute with that discussion by illustrating another possible source of bias due to failure of the screening methods preceding the MPN.
authors: Departamento de Medicina Veterinária Preventiva, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Brazil; Division of Epidemiology and Microbial Genomics, National Food Institute, Technical University of Denmark, Denmark. Electronic address: luis.corbellini@ufrgs.br.
authors: Luís Gustavo
authors: LG
authors: Corbellini
authors: Division of Epidemiology and Microbial Genomics, National Food Institute, Technical University of Denmark, Denmark.
authors: Ana Sofia Ribeiro
authors: AS
authors: Duarte
authors: Division of Epidemiology and Microbial Genomics, National Food Institute, Technical University of Denmark, Denmark.
authors: Leonardo Víctor
authors: LV
authors: de Knegt
authors: Ministério da Agricultura, Pecuária e Abastecimento, Brazil.
authors: Luis Eduardo
authors: LE
authors: da Silva
authors: Departamento de Medicina Veterinária Preventiva, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Brazil.
authors: Marisa
authors: M
authors: Cardoso
authors: Division of Epidemiology and Microbial Genomics, National Food Institute, Technical University of Denmark, Denmark.
authors: Maarten
authors: M
authors: Nauta
mesh_terms: D000818:Animals; D058491:Bacterial Load / Q000592:standards*; D001499:Bayes Theorem; D005511:Food Handling / Q000592:standards; D005516:Food Microbiology / Q000379:methods*; D008460:Meat / Q000382:microbiology*; D011336:Probability; D012475:Salmonella / Q000502:physiology; D012680:Sensitivity and Specificity; D013552:Swine
keywords: Bayesian; Concentration distribution; Food safety; Pork; Quantitative microbiological risk assessment; Salmonella