Ranking the Risks: The 10 Pathogen-Food Combinations With The Greatest Burden on
Authors: Health Michael B. Batz, Sandra Hoffmann and J. Glenn Morris, Jr.
Table of Contents
- Executive Summary
- Chapter 1: Introduction
- Chapter 2: Methodology
- Charper 3: Results
- Chapter 4: Findings and Recommendations
- Appendix A: Rankings of Top 50 Pathogen-Food Combinations
- APPENDIX B: Attribution Data
On January 4, 2011, President Obama signed into law the most far-reaching food safety legislation in over 70 years. The Food Safety Modernization Act (FSMA) mandates a science- and risk-based system built upon the premise that data-driven analysis should inform the efficient targeting of efforts to minimize foodborne illness risks to the American consumer. The National Academy of Sciences (NAS), the U.S. Government Accountability Office (GAO) and others have repeatedly called on the U.S. Food and Drug Administration (FDA) and the Food Safety and Inspection Service of the U.S. Department of Agriculture (USDA FSIS) to become more preventative and risk-based. Achieving this vision will require development of new data and risk-prioritization models to identify high-risk foods and facilities and to inform resource allocation decisions. Tightening budgets make implementation of this vision all the more urgent.
The starting point for implementing risk-based food safety systems is being able to identify where the greatest food safety problems lie. For foodborne illness, the starting point is the question: which pathogens in which foods cause the greatest impact on public health?
The question is easy to ask. Getting a good answer isn’t. The U.S. Centers for Disease Control and Prevention (CDC) estimates that one in six Americans get sick each year from food contaminated by any one of dozens of bacteria, viruses and parasitic protozoa (Scallan et al. 2011a, 2011b). Foodborne pathogens cause not only mild diarrhea, but organ failure, paralysis, neurological impairment, blindness, stillbirths and death. Risk-based prioritization requires having some way to summarize the burden of these diverse conditions into comparable measures of health impact. Furthermore, these illnesses are associated with myriad foods, from poultry to produce to peanut butter, but estimating the association between particular foods and these issues is not straightforward.
To provide a means of comparing the risks posed by different pathogen food combinations in the U.S., we developed a comparable set of estimates of disease burden for 14 leading pathogens across 12 food categories (168 pathogen-food combinations). These fourteen 14 pathogens represent over 95 percent of the annual illnesses and hospitalizations, and almost 98 percent of the deaths, estimated by CDC due to 31 foodborne pathogens (Scallan et al. 2011a). For each pathogen, we estimate health impacts in monetary cost of illness and loss of Quality Adjusted Life Years (QALYs), a measure of health-related quality of life. Both cost of illness and QALY loss are integrated measures of disease burden that allow us to compare pathogens with very different rates of incidence, hospitalization and death, as well as different symptoms and long-term chronic conditions. We attribute these illnesses to foods based on an analysis of eleven years of foodborne outbreak data and a peer-reviewed expert elicitation (Hoffmann et al. 2007). We explain our method in Chapter 2. There are significant uncertainties in the data sources and model assumptions used to obtain our estimates, and therefore in the estimates themselves. Our analysis is constrained by these limitations. Our estimates should be regarded, therefore, as an important starting point in an ongoing process to improve our understanding of the very complex interactions among pathogens and foods in the U.S. food system.
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