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The impact of screening-test negative samples not enumerated by MPN
Luís Gustavo Corbellini1, Ana Sofia Ribeiro Duarte2, Leonardo Víctor de Knegt2
1Departamento 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.
Screening tests for Salmonella in pork can produce false negatives, impacting contamination estimates. Incorporating these false negatives into analysis using Bayesian methods provides a more accurate distribution of Salmonella levels.
Area of Science:
- Food microbiology
- Statistical modeling
- Food safety
Background:
- Microbiological surveys can yield false negatives, affecting microbial enumeration.
- Screening tests are often used before quantitative methods like Most Probable Number (MPN).
- The impact of screening test insensitivity on Salmonella concentration distribution in pork is not fully understood.
Purpose of the Study:
- To evaluate the effect of screening test failures on the probability distribution of Salmonella concentrations in pork.
- To illustrate how false negative results from screening impact Salmonella enumeration.
- To apply a Bayesian method for analyzing Salmonella contamination data.
Main Methods:
- Collected 276 pork swab samples across four slaughter stages.
- Screened samples for Salmonella and enumerated using the MPN method.
- Utilized a Bayesian model to fit Salmonella contamination data to a lognormal distribution, incorporating screening results and false negatives.
Main Results:
- The relative sensitivity of the screening test was determined to be 69%.
- Data sets including false negatives showed higher estimated mean (μ̂) and lower estimated standard deviation (σ̂) compared to those excluding them.
- This indicates that screening test insensitivity influences the estimated distribution of Salmonella contamination.
Conclusions:
- False negative results from screening tests significantly affect the accuracy of Salmonella concentration distribution estimations.
- Failure of preliminary screening methods is a potential source of bias in microbial data analysis.
- Accurate Salmonella risk assessment requires accounting for the limitations of screening tests.
