New Data, Strategies, and Insights for Listeria monocytogenes Dose-Response Models: Summary of an Interagency Workshop, 2011
ABSTRACT Listeria monocytogenes is a leading cause of hospitalization, fetal loss, and death due to foodborne illnesses in the United States. A quantitative assessment of the relative risk of listeriosis associated with the consumption of 23 selected categories of ready-to-eat foods, published by the U.S. Department of Health and Human Services and the U.S. Department of Agriculture in 2003, has been instrumental in identifying the food products and practices that pose the greatest listeriosis risk and has guided the evaluation of potential intervention strategies. Dose-response models, which quantify the relationship between an exposure dose and the probability of adverse health outcomes, were essential components of the risk assessment. However, because of data gaps and limitations in the available data and modeling approaches, considerable uncertainty existed. Since publication of the risk assessment, new data have become available for modeling L. monocytogenes dose-response. At the same time, recent advances in the understanding of L. monocytogenes pathophysiology and strain diversity have warranted a critical reevaluation of the published dose-response models. To discuss strategies for modeling L. monocytogenes dose-response, the Interagency Risk Assessment Consortium (IRAC) and the Joint Institute for Food Safety and Applied Nutrition (JIFSAN) held a scientific workshop in 2011 (details available at http://foodrisk.org/irac/events/). The main findings of the workshop and the most current and relevant data identified during the workshop are summarized and presented in the context of L. monocytogenes dose-response. This article also discusses new insights on dose-response modeling for L. monocytogenes and research opportunities to meet future needs.
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ABSTRACT: Background. In 2011, a multistate outbreak of listeriosis linked to contaminated cantaloupes raised concerns that many pregnant women might have been exposed to Listeria monocytogenes. Listeriosis during pregnancy can cause fetal death, premature delivery, and neonatal sepsis and meningitis. Little information is available to guide healthcare providers who care for asymptomatic pregnant women with suspected L. monocytogenes exposure. Methods. We tracked pregnancy-associated listeriosis cases using reportable diseases surveillance and enhanced surveillance for fetal death using vital records and inpatient fetal deaths data in Colorado. We surveyed 1,060 pregnant women about symptoms and exposures. We developed three methods to estimate how many pregnant women in Colorado ate the implicated cantaloupes, and we calculated attack rates. Results. One laboratory-confirmed case of listeriosis was associated with pregnancy. The fetal death rate did not increase significantly compared to preoutbreak periods. Approximately 6,500–12,000 pregnant women in Colorado might have eaten the contaminated cantaloupes, an attack rate of ∼1 per 10,000 exposed pregnant women. Conclusions. Despite many exposures, the risk of pregnancy-associated listeriosis was low. Our methods for estimating attack rates may help during future outbreaks and product recalls. Our findings offer relevant considerations for management of asymptomatic pregnant women with possible L. monocytogenes exposure.Infectious Diseases in Obstetrics and Gynecology 02/2015; 2015. DOI:10.1155/2015/201479
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ABSTRACT: Quantitative Microbiological Risk Assessment (QMRA) is a structured methodology used to assess the risk involved by ingestion of a pathogen. It applies mathematical models combined with an accurate exploitation of data sets, represented by distributions and - in the case of two-dimensional Monte Carlo simulations - their hyperparameters. This research aims to highlight background information, assumptions and truncations of a two-dimensional QMRA and advanced sensitivity analysis. We believe that such a detailed listing is not always clearly presented in actual risk assessment studies, while it is essential to ensure reliable and realistic simulations and interpretations. As a case-study, we are considering the occurrence of listeriosis in smoked fish products in Belgium during the period 2008-2009, using two-dimensional Monte Carlo and two sensitivity analysis methods (Spearman correlation and Sobol sensitivity indices) to estimate the most relevant factors of the final risk estimate. A risk estimate of 0.018% per consumption of contaminated smoked fish by an immunocompromised person was obtained. The final estimate of listeriosis cases (23) is within the actual reported result obtained for the same period and for the same population. Variability on the final risk estimate is determined by the variability regarding (i) consumer refrigerator temperatures, (ii) the reference growth rate of L. monocytogenes, (iii) the minimum growth temperature of L. monocytogenes and (iv) consumer portion size. Variability regarding the initial contamination level of L. monocytogenes tends to appear as a determinant of risk variability only when the minimum growth temperature is not included in the sensitivity analysis; when it is included the impact regarding the variability on the initial contamination level of L. monocytogenes is disappearing. Uncertainty determinants of the final risk indicated the need of gathering more information on the reference growth rate and the minimum growth temperature of L. monocytogenes. Uncertainty in the dose-response relationship was not included in the analysis, hence the level of its influence cannot be assessed in the present research. Finally, a baseline global workflow for QMRA and sensitivity analysis is proposed.International Journal of Food Microbiology 08/2014; 190C:31-43. DOI:10.1016/j.ijfoodmicro.2014.07.034 · 3.16 Impact Factor
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ABSTRACT: Evaluations of Listeria monocytogenes dose-response relationships are crucially important for risk assessment and risk management, but are complicated by considerable variability across population subgroups and L. monocytogenes strains. Despite difficulties associated with the collection of adequate data from outbreak investigations or sporadic cases, the limitations of currently available animal models, and the inability to conduct human volunteer studies, some of the available data now allow refinements of the well-established exponential L. monocytogenes dose response to more adequately represent extremely susceptible population subgroups and highly virulent L. monocytogenes strains. Here, a model incorporating adjustments for variability in L. monocytogenes strain virulence and host susceptibility was derived for 11 population subgroups with similar underlying comorbidities using data from multiple sources, including human surveillance and food survey data. In light of the unique inherent properties of L. monocytogenes dose response, a lognormal-Poisson dose-response model was chosen, and proved able to reconcile dose-response relationships developed based on surveillance data with outbreak data. This model was compared to a classical beta-Poisson dose-response model, which was insufficiently flexible for modeling the specific case of L. monocytogenes dose-response relationships, especially in outbreak situations. Overall, the modeling results suggest that most listeriosis cases are linked to the ingestion of food contaminated with medium to high concentrations of L. monocytogenes. While additional data are needed to refine the derived model and to better characterize and quantify the variability in L. monocytogenes strain virulence and individual host susceptibility, the framework derived here represents a promising approach to more adequately characterize the risk of listeriosis in highly susceptible population subgroups.Risk Analysis 06/2014; 35(1). DOI:10.1111/risa.12235 · 1.97 Impact Factor