Abstract: The determination of foodborne pathogen concentration is an important prerequisite for quantitative microbial risk assessment (QMRA). The existence of censored data readily causes bias in the estimation of the contamination levels of pathogens in foods. The analysis of censored data has gradually become an important part of the quantitative modeling of foodborne pathogens. This article presents a comprehensive review of recent related studies conducted in China and across the world, introduces readers to the classification of censored data in the detection of foodborne pathogen contamination and compares four commonly used methods for censored data analysis, namely substitution, parameter estimation, non-parametric estimation method and multiple imputation. This article gives a brief overview of the application of pathogen contamination datasets with different characteristics and related statistical methods in the estimation of foodborne pathogen contamination levels. Finally, it discusses the problems currently existing in the estimation of foodborne pathogen contamination levels. While great efforts should be made to reduce the uncertainty of estimation results, the variability of detection data should not be ignored either. This review concludes with an outlook on risk monitoring, risk assessment, and risk communication in the future.

Key words: foodborne pathogen; censored data; quantitative estimation; risk assessment; uncertainty