In two articles in its July 2012 issue, the Journal of Food Protection presents one possible approach to the assessment of the societal “costs” of foodborne illness. While these attempts to measure costs are, at best, somewhat subjective, these articles represent a useful benchmark for future attempts to measure societal impacts.

Copyright restrictions make the complete texts of the articles, of course, only available to researchers with database access. However, we are permitted to present the abstracts below:

Batz, Hoffmann, et al., Ranking the Disease Burden of 14 Pathogens in Food Sources in the United States Using Attribution Data from Outbreak Investigations and Expert Elicitation, Journal of Food Protection, Volume 75, Number 7, July 2012.

Abstract: Understanding the relative public health impact of major microbiological hazards across the food supply is critical for a risk-based national food safety system. This study was conducted to estimate the U.S. health burden of 14 major pathogens in 12 broad categories of food and to then rank the resulting 168 pathogen-food combinations. These pathogens examined were Campylobacter, Clostridium perfringens, Escherichia coli O157:H7, Listeria monocytogenes, norovirus, Salmonella enterica, Toxoplasma gondii, and all other FoodNet pathogens. The health burden associated with each pathogen was measured using new estimates of the cost of illness and loss of quality-adjusted life years (QALYs) from acute and chronic illness and mortality. A new method for attributing illness to foods was developed that relies on both outbreak data and expert elicitation. This method assumes that empirical data are generally preferable to expert judgment; thus, outbreak data were used for attribution except where evidence suggests that these data are considered not representative of food attribution. Based on evaluation of outbreak data, expert elicitation, and published scientific literature, outbreak-based attribution estimates for Campylobacter, Toxoplasma, Cryptosporidium, and Yersinia were determined not representative; therefore, expert-based attribution were included for these four pathogens. Sensitivity analyses were conducted to assess the effect of attribution data assumptions on rankings. Disease burden was concentrated among a relatively small number of pathogen-food combinations. The top 10 pairs were responsible for losses of over $8 billion and 36,000 QALYs, or more than 50 % of the total across all pairs. Across all 14 pathogens, poultry, pork, produce, and complex foods were responsible for nearly 60 % of the total cost of illness and loss of QALYs.


Hoffmann, Batz, et al., Annual Cost of Illness and Quality-Adjusted Life Year Losses in the United States Due to 14 Foodborne Pathogens, Journal of Food Protection, Volume 75, Number 7, July 2012.

Abstract: In this article we estimate the annual cost of illness and quality-adjusted life year (QALY) loss in the United States caused by 14 of the 31 major foodborne pathogens reported on by Scallan et al. (Emerg. Infect. Dis. 17:7-15, 2011), based on their incidence estimates of foodborne illness in the United States. These 14 pathogens account for 95 % of illnesses and hospitalizations and 98 % of deaths due to identifiable pathogens estimated by Scallan et al. We estimate that these 14 pathogens cause $14.0 billion (ranging from $4.4 billion to $33.0 billion) in cost of illness and a loss of 61,000 QALYs (ranging from 19,000 to 145,000 QALYs) per year. Roughly 90 % of this loss is caused by five pathogens: nontyphoidal Salmonella enterica ($3.3 billion; 17,000 QALYs), Campylobacter spp. ($1.7 billion; 13,300 QALYs), Listeria monocytogenes ($2.6 billion; 9,400 QALYs), Toxoplasma gondii ($3 billion; 11,000 QALYs), and norovirus ($2 billion; 5,000 QALYs). A companion article attributes losses estimated in this study to the consumption of specific categories of foods. To arrive at these estimates, for each pathogen we create disease outcome trees that characterize the symptoms, severities, durations, outcomes, and likelihoods of health states associated with that pathogen. We then estimate the cost of illness (medical costs, productivity loss, and valuation of premature mortality) for each pathogen. We also estimate QALY loss for each health state associated with a given pathogen, using the EuroQol 5D scale. Construction of disease outcome trees, outcome-specific cost of illness, and EuroQol 5D scoring are described in greater detail in a second companion article.