Analysis estimates $370.8 billion in societal costs from food allergy in the US, highlighting disparities among underserved populations.
Food allergy (FA) imposes a large burden on patients/caregivers, but there is limited recent information on the societal economic burden of FA. We aimed to quantify this burden in the United States (US) using a health economic population cost exercise. A prevalence-based model was adopted to estimate the US population with FA and the annual societal/patient costs of FA (in 2024 US$). The Markov model consisted of 3 mutually exclusive health states: 'avoidance (with sensitivity)', 'full tolerance', and death. Inputs included published data on epidemiology, clinical outcomes, and estimated costs. The model focuses on a comprehensive societal scenario. Scenario analyses utilized a conservative costing approach, determined if the estimated burden exhibited heterogeneity across underserved populations of race/ethnicity and household income, and assessed the impact of allergen desensitization on estimated costs. The model estimated 16,678,832 people with ≥1 physician-diagnosed FA, an annual total societal cost of $370.8 billion, and an annual cost per patient of $22,234, which was higher for children and adolescents than adults. Societal cost was primarily attributed to indirect costs (92.7% of total cost). In the scenario analysis, conservative total societal cost was $39.6 billion; Hispanic, African American, and other races/multiracial patients had ∼3% increased cost relative to White patients; direct medical cost for the low-income group was 39.1% higher than for the high-income group; and total cost was reduced by ∼4% for each additional 10% of the population that entered the model as desensitized. Using a population cost exercise that incorporated a range of epidemiologically plausible explanations, we estimated the annual total societal cost of FA in the US may approach $370.8 billion, mostly from indirect costs borne by patients/caregivers during daily living. This assessment may assist population-level healthcare decision-makers in investing in measures that reduce economic burden, valuing interventions, and considering approaches to reduce economic/health disparities for underserved populations.
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Warren et al. (2025) studied this question.
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