Regional Association of Disability and SARS-CoV-2 Infection in 369 Counties of the United States

  1. Oluwaseyi Olulana
  2. Vida Abedi
  3. Venkatesh Avula
  4. Durgesh Chaudhary
  5. Ayesha Khan
  6. Shima Shahjouei
  7. Jiang Li
  8. Ramin Zand

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

There have been outbreaks of SARS-CoV-2 in long term care facilities and recent reports of disproportionate death rates among the vulnerable population. The goal of this study was to better understand the impact of SARS-CoV-2 infection on the non-institutionalized disabled population in the United States using data from the most affected states as of April 9th, 2020.

Methods

This was an ecological study of county-level factors associated with the infection and mortality rate of SARS-CoV-2 in the non-institutionalized disabled population. We analyzed data from 369 counties from the most affected states (Michigan, New York, New Jersey, Pennsylvania, California, Louisiana, Massachusetts) in the United States using data available by April 9th, 2020. The variables include changes in mobility reported by Google, race/ethnicity, median income, education level, health insurance, and disability information from the United States Census Bureau. Bivariate regression analysis adjusted for state and median income was used to analyze the association between death rate and infection rate.

Results

The independent sample t-test of two groups (group 1: Death rate≥3.4% [median] and group 2: Death rate < 3.4%) indicates that counties with a higher total population, a lower percentage of Black males and females, higher median income, higher education, and lower percentage of disabled population have a lower rate (< 3.4%) of SARS-CoV-2 related mortality (all p- values<4.3E-02). The results of the bivariate regression when controlled for median income and state show counties with a higher White disabled population (est: 0.19, 95% CI: 0.01-0.37; p-value :3.7E-02), and higher population with independent living difficulty (est: 0.15, 95% CI: −0.01-0.30; p-value : 6.0E-02) have a higher rate of SARS-CoV-2 related mortality. Also, the regression analysis indicates that counties with higher White disabled population (est: - 0.22, 95% CI: −0.43-(-0.02); p- value: 3.3E-02), higher population with hearing disability (est: −0.26, 95% CI: - 0.42- (-0.11); p -value:1.2E-03), and higher population with disability in the 18-34 years age group (est: −0.25, 95% CI: −0.41-(-0.09); p -value:2.4E-03) show a lower rate of SARS-CoV-2 infection.

Conclusion

Our results indicate that while counties with a higher percentage of non-institutionalized disabled population, especially White disabled population, show a lower infection rate, they have a higher rate of SARS-CoV-2 related mortality.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.06.24.20139212: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data source: Data sources in this study include publicly available data from United States Census Bureau data estimated for 2018 for demographic data per county12,13 USAFacts for SARS-CoV-2 cases estimated for the year 2020,14 and mobility data provided by Google, as of April 5th, 2020.15 According to Social Security, individuals who cannot engage in substantial productive activity due to medically diagnosable physical or mental impairment which is expected to lead to death or last for over twelve months are legally defined as disabled.
    Google
    suggested: (Google, RRID:SCR_017097)
    Statistical analyses were performed using the IBM SPSS Statistics 2618 and R version 3.6.2.19
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Another reason for the high mortality rates could be due to the independent living difficulty that may have been compounded by the pandemic such as transportation limitations, grocery access, reduced opportunity for daily care, and essential services.25 Additionally, in anticipation of a supply crisis, many health departments around the U.S. considered options on how to triage patients who should be given the most aggressive life-saving therapies in the event of a supply shortage.26 In Washington state, a plan was put forward to withhold advanced care for patients with heart failure, chronic lung and liver disease among other organ dysfunctions; diseases that are common co-morbidities with the adult disabled population.26–28 Although this action was not officially taken in the U.S, there is a history of systematic discrimination in policies and treatment of disabled patients and lack of adequate preparedness for disabled patients during a pandemic.23 The center for disease control and prevention (CDC) cautioned that difficulty to understand information, limited mobility, and inability to communicate symptoms/illness may put the disabled patient population at risk.29 Alternatively, our results when adjusted for state and median income show counties with higher White disabled population and higher hearing disabled population have a lower rate of SARS-CoV-2 infection. There is a possibility that people with a hearing disability are overcompensated with visual information,30 whic...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.06.24.20139212v1 on medRxiv