Power in numbers: quantitative microbial risk assessments of Salmonella in federally sampled ground meat products and the resulting impact of risk management strategies on public health

Salmonellosis is the most common bacterial foodborne illness in the United States, and it is estimated that more than 40% of annual illnesses are attributable to the consumption of contaminated meat products. Incidence rates have not declined over the last 15 years in the US despite a significant Salmonella prevalence reduction in meat and poultry products. The USDA Food Safety and Inspection Service (FSIS) - the agency tasked with ensuring that meat, poultry, and egg products are safe, wholesome, and properly labeled - use qualitative pathogen prevalence testing to monitor Salmonella in the commodity meat products that they regulate. Current FSIS product performance standards are based entirely on pathogen presence or absence. However, novel quantitative Salmonella enumeration methods are emerging with advances in food sampling technologies resulting in more timely, less costly pathogen characterization. Pathogen enumeration allows risk assessors to use dose-response relationships to directly link an ingested dose to the likelihood of a consumer experiencing a health outcome (often illness or death).This dissertation explores the use of quantitative Salmonella enumeration of federally sampled meat products to predict the overall public health impact of product contamination. Quantitative microbial risk assessment (QMRA) models that contextualized common handling, preparation, and consumption practices were developed to estimate annual illnesses attributable to the consumption of contaminated ground beef and ground pork in the US. Modifications to model parameters also predicted the effect of various risk management strategies such as the removal of highly contaminated production lots, highly virulent serotypes, and multidrug-resistant organisms. Finally, cross-contamination events in kitchen preparation settings were incorporated into risk models to identify any additional risk to consumers in the post-retail phase of the product supply chain. Findings from these studies highlight the opportunities stemming from the integration of modernized enumeration techniques into pathogen surveillance systems. Identifying the most impactful risk prevention strategies allows for the development of performance standards that aim to directly improve public health outcomes. Achieving federal salmonellosis reduction goals requires a paradigm shift that prioritizes risk-based thinking in Salmonella management interventions.

Author dc:creator

• Strickland, Ali

• Assessment
• Enumeration
• Foodborne
• Multidrug-resistance
• Risk
• Salmonella

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/11299/276823

OAI identifier oai:identifier

oai:conservancy.umn.edu:11299/276823