Risk Analysis, Vol. 25, No. 5, 2005 DOI: 10.1111/j.1539-6924.2005.00665.x Stochastically Modeling Listeria Monocytogenes Growth in Farm Tank Milk Isabelle Albert, 1* R´ egis Pouillot, 2 and Jean-Baptiste Denis 3 This article presents a Listeria monocytogenes growth model in milk at the farm bulk tank stage. The main objective was to judge the feasibility and value to risk assessors of introduc- ing a complex model, including a complete thermal model, within a microbial quantitative risk assessment scheme. Predictive microbiology models are used under varying temperature conditions to predict bacterial growth. Input distributions are estimated based on data in the literature, when it is available. If not, reasonable assumptions are made for the considered context. Previously published results based on a Bayesian analysis of growth parameters are used. A Monte Carlo simulation that forecasts bacterial growth is the focus of this study. Three scenarios that take account of the variability and uncertainty of growth parameters are com- pared. The effect of a sophisticated thermal model taking account of continuous variations in milk temperature was tested by comparison with a simplified model where milk temperature was considered as constant. Limited multiplication of bacteria within the farm bulk tank was modeled. The two principal factors influencing bacterial growth were found to be tank ther- mostat regulation and bacterial population growth parameters. The dilution phenomenon due to the introduction of new milk was the main factor affecting the final bacterial concentration. The results show that a model that assumes constant environmental conditions at an average temperature should be acceptable for this process. This work may constitute a first step to- ward exposure assessment for L. monocytogenes in milk. In addition, this partly conceptual work provides guidelines for other risk assessments where continuous variation of a parameter needs to be taken into account. KEY WORDS: Listeria monocytogenes; Monte Carlo simulation; quantitative microbial risk assessment; stochastic growth model; variability/uncertainty 1. INTRODUCTION Listeria monocytogenes is a well-known food- borne pathogen; it has been extensively studied since the beginning of the 1980s, following the first recog- 1 Met@risk Unit, Food Risk Methodologies, INRA, National Insti- tute for Agricultural Research, France. 2 French Food Safety Agency, Maisons-Alfort, France. Current af- filiation: Centre Pasteur du Cameroon, Yaound´ e, Cameroon. 3 Applied Mathematics and Informatics Unit, INRA, National In- stitute for Agricultural Research, France. ∗ Address correspondence to Isabelle Albert, INA P-G, 16 rue Claude Bernard 75231 Paris Cedex 05, France; albert@ inapg.inra.fr. nized outbreak. (1) Risk assessment is necessary to fa- cilitate the management of this major economic and public health hazard. Microbial risk assessment is complicated by potential fluctuations in the bacterial population as a function of environment, from food production to ingestion. Bacterial concentrations vary because of the growth and death of microorganisms as a result of environmental conditions throughout the process. Mathematical models have been devel- oped in the last few decades that can describe and predict the growth of microbial populations as a function of environmental factors. (2) These models thus need to be included in microbial food safety 1171 0272-4332/05/0100-1171$22.00/1 C  2005 Society for Risk Analysis