The Economic Cost of Foodborne Illness

Non-Technical Summary: <BR>The CDC estimates that foodborne contaminants are responsible for approximately 48 million domestically acquired illnesses each year. Given that there is no single intervention that will serve to completely eliminate foodborne illness, food safety initiatives often employ a farm-to-table approach. Options for reducing foodborne illness exist pre-harvest, in the post-harvest processing stage, during transportation, at the retail level, and in the home. Not all available options are feasible, especially in an economic and budgetary climate unfavorable to regulation and regulators. Accordingly, costly government programs designed to reduce foodborne illness are coming under increased scrutiny by those seeking to trim budgets. In response, there has been growing demand for economic evaluations (a.k.a. benefit-cost analyses) of not just regulatory proposals, but also of entire food safety programs. This is occurring at the Federal, state, and local levels. Furthermore, concurrent with the increased demand, new CDC estimates for the burden of illness have rendered as obsolete all economic analyses based on past estimates. The primary significance of my proposed research program is that it will result in updated comprehensive pathogen and population-specific estimates for the cost of foodborne illness that can be readily used to evaluate the efficacy of food safety interventions and programs. Although I have designed my research program to add to the comprehensiveness and flexibility of my model over time, I have also planned to have basic updated estimates ready for use in the near future. The data generated from this project can be used to ensure that resources are directed towards effective food safety programs and inform the design of these programs. The net result will be a better distribution of scarce resources and, as a result, improvement in human health. <P> Approach: <BR> Objective 1: The first objective of this project is to develop new models to provide empirical estimates for economic costs not currently included in cost of foodborne illness models. Generalizable estimates of the cost of foodborne illness for industry participants and the public health sector do not exist. For this reason, current estimates limited to health-related costs likely underestimate the true cost of foodborne illness. Assessing these costs is difficult. For industry, there are costs associated with recalls, facility clean-up, litigation, and lost sales due to reputation effects. For the public health sector, there is the cost of following up on reported illnesses, testing food and stool samples, litigating enforcement actions, and managing recalls. To assess pathogen specific costs for each category, I will first examine the possibility of performing a meta-analysis on the case reports that exist in the literature. After a thorough literature review, I should know whether this is possible. If this approach is not fruitful, it is likely that I will have to seek funding to conduct a survey of representative industry members and/or public health authorities to directly assess costs. I will also explore alternative means of estimating these costs. Objective 2: To complete the second objective I will develop models to examine the heterogeneity of costs for food safety across individuals and communities. Food safety programs are employed by all levels of government and targeted towards many distinct population groups. Given that there are significant differences in costs for different populations, it is important to have cost of illness estimates that can be tailored for use with a specific group. Where important costs vary significantly by population, cost of illness estimates will be derived to reflect characteristics such as age, state of residence, and residence in an urban or rural area. Some cost differences are relatively easily measured using data from government databases. Others involve econometric analysis of secondary data. Still others may require that an original data collection be undertaken. For this objective I anticipate that I will be able to make significant progress without the collection of primary data. Objective 3 and 4: For objectives 3 and 4 I will provide new comprehensive estimates for the economic cost of foodborne illness and use the updated empirical model in economic evaluations of food safety interventions. As objectives 1 and 2 are completed, the data generated will be integrated with the existing cost of illness model. This model will be restructured to allow for manipulation of important population variables, such as age, state, and residence in a rural community. Estimates reflecting both the basic model used by ERS and the enhanced model used by FDA will be generated by the model. Uncertainty will be expressed through distributions generated using Monte Carlo analysis in @Risk 5.5. Ultimately, I will elicit opportunities to use the model to evaluate food safety interventions and/or programs.