Time valuation of historical outbreak attribution data.

Human illness attribution is recognized as an important metric for prioritizing and informing food-safety decisions and for monitoring progress towards long-term food-safety goals. Inferences regarding the proportion of illnesses attributed to a specific commodity class are often based on analyses of datasets describing the number of outbreaks in a given year or combination of years. In many countries, the total number of pathogen-related outbreaks reported nationwide for an implicated food source is often fewer than 50 instances in a given year and the number of years for which data are available can be fewer than 10. Therefore, a high degree of uncertainty is associated with the estimated fraction of pathogen-related outbreaks attributed to a general food commodity. Although it is possible to make inferences using only data from the most recent year, this type of estimation strategy ignores the data collected in previous years. Thus, a strong argument exists for an estimator that could 'borrow strength' from data collected in the previous years by combining the current data with the data from previous years. While many estimators exist for combining multiple years of data, most either require more data than is currently available or lack an objective and biologically plausible theoretical basis. This study introduces an estimation strategy that progressively reduces the influence of data collected in past years in accordance with the degree of departure from a Poisson process. The methodology is applied to the estimation of the attribution fraction for Salmonella and Escherichia coli O157:H7 for common food commodities and the estimates are compared against two alternative estimators.

An overview of the Salmonella enteritidis risk assessment for shell eggs and egg products.

This article summarizes a quantitative microbial risk assessment designed to characterize the public health impact of consumption of shell eggs and egg products contaminated with Salmonella Enteritidis (SE). This risk assessment's objectives were to: (1) establish the baseline risk of foodborne illness from SE, (2) identify and evaluate potential risk mitigation strategies, and (3) identify data gaps related to future research efforts. The risk assessment model has five modules. The Egg Production module estimates the number of eggs produced that are SE-contaminated. Shell Egg Processing, Egg Products Processing, and Preparation & Consumption modules estimate the increase or decrease in the numbers of SE organisms in eggs or egg products as they pass through storage, transportation, processing, and preparation. A Public Health Outcomes module then calculates the incidence of illnesses and four clinical outcomes, as well as the cases of reactive arthritis associated with SE infection following consumption. The baseline model estimates an average production of 2.3 million SE-contaminated shell eggs/year of the estimated 69 billion produced annually and predicts an average of 661,633, human illnesses per year from consumption of these eggs. The model estimates approximately 94% of these cases recover without medical care, 5% visit a physician, an additional 0.5% are hospitalized, and 0.05% result in death. The contribution of SE from commercially pasteurized egg products was estimated to be negligible. Five mitigation scenarios were selected for comparison of their individual and combined effects on the number of human illnesses. Results suggest that mitigation in only one segment of the farm-to-table continuum will be less effective than several applied in different segments. Key data gaps and areas for future research include the epidemiology of SE on farms, the bacteriology of SE in eggs, human behavior in food handling and preparation, and human responses to SE exposure.