County Demographics and COVID-19 Death Rates: Comparison of relationship in the first and current stage of the pandemic in the United States of America

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Abstract

Previous studies have discovered disparity in death rates associated with SARS-CoV-2 infection in the United States during the initial stages of the pandemic. Specifically, the death rates were higher in the population in poverty and communities of color across the United States. In the current study, we perform the secondary analysis of death rates due to COVID-19 data, obtained from the Center for Disease Control and Prevention (CDC). Results indicate that in the first phase of the pandemic (February 1 to August 1, 2020), counties with higher percentage of White, Native Hawaiian and other Pacific Islanders, and two or more races populations were found to have lower per-capita COVID-19 death rate. Whereas counties with population having higher percentage of females, Black or African American people, and persons in poverty had higher death rates. Analysis of the death rates from August 1 to September 10, 2020, indicate that disparity continues with counties having higher population of Black or African American people and female having higher death rates. Poverty is not a significant variable in determining the death rates due to COVID-19. Based on the current data and lack of detailed molecular mechanism of the disease, we suggest that more resources must be diverted to counties with higher percentages of Black or African American and female populations.

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  1. SciScore for 10.1101/2020.11.24.20237818: (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 variableCensus Bureau database.7 The demographic variables (independent variables) included were i) sex (percentage female population), ii) race (percentage of White, Black or African American, Asian, Native Hawaiian and other Pacific Islanders, American Indian and Alaska Native, Hispanic or Latino, and two or more races), and iii) income and poverty (median household income, per capita income, and percentage person in poverty).

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Poisson regression analysis was performed using Minitab 18 software.
    Minitab
    suggested: (Minitab, RRID:SCR_014483)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.