Analyzing county-wide trends in Tennessee Covid-19 rates, Median Household Income, and Presence of Hospital

  1. Viraj Brahmbhatt

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Abstract

The Covid-19 pandemic has caused millions of deaths and infections worldwide. Recent studies suggest that Covid-19 may be disproportionately affecting certain groups. The Tennessee Department of Health regularly publishes data on Covid infections and vaccinations. This data alongside data published from the 2010 census was used to analyze trends in Covid-19 rates for the State of Tennessee. The census data for the average household income of each county was cross-referenced with the covid data. A positive correlation between population of the county and the number of new cases reported on January 3 rd , 2022, appeared when observing the data. A regression analysis (ANOVA) revealed that the data on population and covid rate was significant (P-value: 2.69E-10). The results from comparing the covid rates in a county with a hospital and a county without a hospital seemed to be the most significant. The data reported by the Sycamore institute on the Tennessee counties without a hospital was used to identify trends unique to these counties. The counties lacking a hospital were compared with counties with a similar population. 7 hospital-less counties were used for comparison, 6 counties (Fayette, Grainger, Haywood, Chester, Sequatchie, Clay) reported a greater number of cases than counties of a similar population. Of the 20 counties lacking a hospital, 16 fell within the bottom 50% of median household incomes, with 9 in the bottom 25% and 4 in the bottom 10%. Healthcare sites in rural areas may lack fundamental infrastructure. These areas may require unique interventions to address the healthcare concerns present.

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    SciScore for 10.1101/2022.03.02.22271656: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Microsoft Excel was used to categorize and analyze the data.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    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.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  2. Version published to 10.1101/2022.03.02.22271656 on medRxiv