Abstract
Background: Migraine is a highly prevalent and incapacitating neurological disorder associated with the highest global disability burden in people aged 15 to 49 years. Europe has the fourth-highest prevalence of migraine, after North America, South America, and Central America, and above Asia and Africa. Migraine leads to relatively modest direct healthcare expenditure but has substantial indirect costs due to reduced productivity. Methods: The economic burden of migraine was estimated in comparison with the general population of the United Kingdom (UK) using an analytical fiscal modeling framework applying the government cost perspective. Published measures of migraine's impact on labor participation were applied to rates of economic activity/inactivity of the general population. The model estimates lifetime changes to earnings from employment, direct and indirect taxes paid, and financial support requirements over the life course. Incremental differences between those affected and unaffected by migraine are reported as net fiscal consequences to public accounts. Fiscal costs are reported as the discounted average per capita over a 20-year time horizon and for the entire annual UK cohort with prevalent migraine. Results: People affected by migraine are more likely to be absent from work, unemployed, and disabled, and to retire early. A 44-year-old individual affected by migraine was associated with £19 823 in excess fiscal costs to the UK government, £1379 per year living with the condition, compared with someone not affected by the disease. Annually, migraine was estimated to represent £12.20 billion to the public economy, approximately £130.63 per migraine episode. The model predicted annual productivity losses in the health and social care workforce to be £2.05 billion and total annual productivity losses to be over £5.81 billion. Conclusions: This fiscal analysis monetizes the occupational consequences of migraine to the UK government, both in terms of lost tax revenue and transfer payments. The findings are substantial and useful to characterize disease severity and to inform the body of evidence considered by decision makers appraising the cost-effectiveness of health technologies.