Determining relationships between the seasonal occurrence of Escherichia coli O157:H7 in live cattle, ground beef, and humans.

The prevalence and concentration of many foodborne pathogens exhibit seasonal patterns at different stages of the farm-to-table continuum. Escherichia coli O157:H7 is one such pathogen. While numerous studies have described the seasonal trend of E. coli O157:H7 in live cattle, ground beef, and human cases, it is difficult to relate the results from these different studies and determine the interrelationships that drive the seasonal pattern of beef-related human illnesses. This study uses a common modeling approach, which facilitates the comparisons across data sets, to relate prevalence in live cattle to raw ground beef and human illness. The results support an intuitive model where a seasonal rise of E. coli O157:H7 in cattle drives increased ground beef prevalence and a corresponding rise in the human case rate. We also demonstrate the use of these models to assess the public health impact of consumer behaviors. We present an example that suggests that the probability of illness, associated with summertime cooking and handling practices, is not substantially higher than the baseline probability associated with more conventional cooking and handling practices during the remainder of the year.

Streamlined analysis for evaluating the use of preharvest interventions intended to prevent Escherichia coli O157:H7 illness in humans.

The U.S. Department of Agriculture Food Safety Inspection Service is responsible for ensuring the safety of meat, poultry, and egg products consumed in the United States. Here we describe a risk assessment method that provides quantitative criteria for decision makers tasked with developing food safety policies. To demonstrate the utility of this method, we apply it to a hypothetical case study on the use of an Escherichia coli O157:H7 cattle vaccine to prevent human illness caused by consuming beef. A combination of quantitative risk assessment methods and marginal economic analysis are used to describe the maximum cost per unit that would still allow the vaccine to be a cost-effective intervention as well as the minimum effectiveness it could have at a fixed cost. We create two economic production functions where the input is number of vaccinated cattle and the output is human illnesses prevented. The production functions are then used for marginal economic analysis to assess the cost/benefit ratio of using the vaccine to prevent foodborne illness. In our case study, it was determined that vaccinating the entire U.S. herd at a cost of between $2.29 and $9.14 per unit (depending on overall effectiveness of the vaccine) would be a cost-effective intervention for preventing E. coli O157:H7 illness in humans. In addition, we determined that vaccinating only a given fraction of the herd would be cost effective for vaccines that are less effective or more costly. For example, a vaccine costing $9.00 per unit that had a 100% efficacy but required 100% herd coverage for immunity would be cost effective for use in about 500,000 cattle each year-equating to an estimated 750 human illnesses prevented per annum. We believe this approach could be useful for public health policy development in a wide range of applications.

Genomics-based food-borne pathogen testing and diagnostics: possibilities for the U.S. Department of Agriculture's Food Safety and Inspection Service.

The use of genomic technologies at the U.S. Department of Agriculture could enhance inspection, monitoring, and risk assessment capabilities within its Food Safety and Inspection Service (FSIS). Molecular assays capable of detecting hundreds of microbial DNA sequences within a single food sample that identify food-borne pathogens of concern and characterize their traits most relevant to human health risk are of great interest for FSIS. For example, a high-density assay, or combination of assays, could screen FSIS inspected food for pathogens relevant to public health (e.g., Salmonella, Listeria, and toxic E. coli) as well as their associated virulence factors and antibiotic resistance genes. Because most genotype assays can be completed in one working day with a minimum of reagents, use of such assays could potentially save FSIS a significant amount of cost/time for analyses. Further, a genotype assay can detect specific microbial traits relevant to human health risk based on the DNA sequence of toxin producing genes, antibiotic resistance alleles, and more. By combining rapid analysis with specific data on human health risks, information from such high-density genotype assays could provide expanded support for test and hold situations, recalls, outbreak management, and microbial risk assessments (e.g., provide data needed for food-borne illness source attribution). Environ. Mol. Mutagen.