Social inequities in the distribution of COVID-19: An intra-categorical analysis of people with disabilities in the U.S

Background: While recent reports suggest that people with disabilities (PwDs) are likely to be adversely impacted by COVID-19 and face multiple challenges, previous research has not examined if COVID-19 burdens are unequally distributed with respect to the disability characteristics of the U.S.

Objective: This article presents the first national scale study of the relationship between COVID-19 incidence and disability characteristics in the U.S. The objective is to determine whether COVID-19 incidence is significantly greater in counties containing higher percentages of socio-demographically disadvantaged PwDs, based on race, ethnicity, poverty status, age, and biological sex.

Methods: This study integrates county-level data on confirmed COVID-19 cases from the Johns Hopkins Center for Systems Science and Engineering database with multiple disability variables from the 2018 American Community Survey. Statistical analyses are based on bivariate correlations and multivariate generalized estimating equations that consider spatial clustering in the data.

Results: Greater COVID-19 incidence rate is significantly associated with: (1) higher percentages of PwDs who are Black, Asian, Hispanic, Native American, below poverty, under 18 years of age, and female; and (2) lower percentages of PwDs who are non-Hispanic White, above poverty, aged 65 or more years, and male, after controlling for spatial clustering.

Conclusions: Socio-demographically disadvantaged PwDs are significantly overrepresented in counties with higher COVID-19 incidence compared to other PwDs. These findings represent an important starting point for more detailed investigation of the disproportionate impacts of COVID-19 on PwDs and highlight the urgent need for COVID-19 data collection systems to incorporate disability information.