Health and Demographic Impact on COVID-19 Infection and Mortality in US Counties

  1. Zidian Xie
  2. Dongmei Li

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Abstract

Introduction

With the pandemic of COVID-19, the number of confirmed cases and related deaths are increasing in the US. We aimed to understand the potential impact of health and demographic factors on the infection and mortality rates of COVID-19 at the population level.

Methods

We collected total number of confirmed cases and deaths related to COVID-19 at the county level in the US from January 21, 2020 to April 23, 2020. We extracted health and demographic measures for each US county. Multivariable linear mixed effects models were used to investigate potential correlations of health and demographic characteristics with the infection and mortality rates of COVID-19 in US counties.

Results

Our models showed that several health and demographic factors were positively correlated with the infection rate of COVID-19, such as low education level and percentage of Black. In contrast, several factors, including percentage of smokers and percentage of food insecure, were negatively correlated with the infection rate of COVID-19. While the number of days since first confirmed case and the infection rate of COVID-19 were negatively correlated with the mortality rate of COVID-19, percentage of elders (65 and above) and percentage of rural were positively correlated with the mortality rate of COVID-19.

Conclusions

At the population level, health and demographic factors could impact the infection and mortality rates of COVID-19 in US counties.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.06.20093195: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Experimental Models: Organisms/Strains
    SentencesResources
    Demographic factors include: percentage of less than 18 years of age, percentage of 65 and over, percentage of Black, percentage of American Indian & Alaska Native, percentage of Asian, percentage of Native Hawaiian/Other Pacific Islander, percentage of Hispanic, percentage of Non-Hispanic White, percentage of not proficient in English, percentage of female, percentage of rural, percentage of adults with a high school or less education, population in 2018, population density (# people per square miles).
    Non-Hispanic White
    suggested: None
    Software and Algorithms
    SentencesResources
    Some county-level information (such as the population and land area in 2018, economic typology in 2015) are downloaded from United States Census Bureau (https://www.census.gov) and USDA Economic Research Service (https://www.ers.usda.gov/data-products/county-level-data-sets/download-data/).
    https://www.census.gov
    suggested: (U.S. Census Bureau, RRID:SCR_011587)
    Outcome Variables and Covariates: The outcome variables include the infection rate of COVID-19 (the number of confirmed cases divided by the population), and the mortality rate of COVID-19 (the number of deaths divided by the number of confirmed cases) in each US county.
    Covariates
    suggested: None
    All analyses were conducted using proc mixed procedure in SAS V.9.4 (SAS Institute Inc.
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    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

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  2. Version published to 10.1101/2020.05.06.20093195 on medRxiv