T6-11 Estimates for the Cost of Foodborne Illness across U.S. States

Tuesday, August 5, 2014: 11:30 AM
Room 203-204 (Indiana Convention Center)
Robert Scharff, The Ohio State University, Columbus, OH
Introduction: Understanding the costs associated with foodborne illnesses is important to policymakers both as a way to prioritize resources for harm mitigation and as a tool in assessing whether proposed interventions improve social welfare. At the national level, multiple methods of assessing costs have been used by Federal food safety regulatory agencies in regulatory impact analyses. The use of national estimates by state policymakers may result in incorrect assessments of costs, possibly leading to inefficient resource allocation. 

Purpose: The purpose of this study was to use three methods of measuring foodborne illness costs to generate state-level costs.

Methods: Federal estimates for the number and severity of illnesses for each pathogen in each state are used.  Three methods are used to assess costs. The most conservative of these methods uses only medical costs and productivity losses to estimate costs.  The most comprehensive method uses adjusted value of statistical life (VSL) estimates to approximate non-financial utility losses associated with illness and death. A third model uses VSL estimates for deaths, but not for nonfatal illnesses. Costs for medical care and productivity losses are based on publically available state-specific medical cost and compensation cost data. Costs for the VSL are based on a meta-analysis, adjusted for differences in state income.

Results: Numerous estimates were derived. For example, medical costs for an average case of foodborne illness range from a low of $90 in West Virginia to a high of $150 in New Jersey, while medical costs associated with Vibrio vulnificus are much higher, ranging from $25,700 in Maryland to $62,000 in New Jersey. Similar estimates were derived for each pathogen and cost category.

Significance: Foodborne illness cost estimates vary significantly by state and method, suggesting careful use of the most relevant estimates.