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Growing Financial Hardship in the United States: A Case of Long COVID

Sun, August 9, 12:00 to 1:00pm, TBA

Abstract

Long COVID has emerged as a widespread and disabling condition, yet its economic consequences for the affected individuals remain insufficiently understood. Existing research has largely focused on employment outcomes or aggregate income loss, with limited attention to how Long COVID shapes broader financial strain and how these effects are distributed across intersecting social positions. Drawing on data from over 1.2 million respondents in the U.S. Census Bureau’s Household Pulse Survey, this study examines the association between Long COVID and three interrelated economic outcomes: labor force participation, household income, and financial strain. Financial strain was operationalized using a latent class–derived ordinal measure capturing multiple dimensions of economic hardship. Logistic and ordinal regression models were estimated in four nested stages, incorporating interactions between COVID status, gender, and race/ethnicity, as guided by the Social Model of Disability and an intersectionality framework. Results show that across all three outcomes, Long COVID was associated with significantly worse economic conditions compared to COVID-only and never-infected individuals. Gender and racial inequalities structured these effects: women and nonbinary individuals exhibited higher baseline economic vulnerability, while men experienced a larger marginal employment penalty associated with Long COVID. Racially marginalized groups, particularly Black, Hispanic, and multiracial individuals, faced disproportionately high levels of financial strain, patterns that largely persisted even after accounting for income. Together, these findings indicate that Long COVID both reinforces existing inequalities and produces new forms of hardship linked to chronic illness, underscoring the need for policy responses that treat Long COVID as a disability-related economic risk rather than solely a medical condition.

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