Ethnics and economics in COVID-19: Meta-regression of data from countries in the New York metropolitan area

  1. Hisato Takagi
  2. Toshiki Kuno
  3. Yujiro Yokoyama
  4. Hiroki Ueyama
  5. Takuya Matsushiro
  6. Yosuke Hari
  7. Tomo Ando

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Abstract

Ethnics and economics may affect prevalence and case fatality of Coronavirus disease 2019 (COVID-19). To determine whether COVID-19 prevalence and fatality are modulated by ethnics and economics, meta-regression of data from the countries in the New York metropolitan area were herein conducted. We selected 31 countries in the New York metropolitan area. 1) Prevalence and case-fatality rates of confirmed COVID-19 cases on May 20, 2020 and 2) income and poverty estimates were obtained in each country. We performed random-effects meta-regression using OpenMetaAnalys. The covariates included 1) black (%), 2) Hispanic or Latino (%), 3) poverty rates (%), and 4) median household income ($). Statistically significant ( P < .05) covariates in the univariable model were together entered into the multivariable model. A slope (coefficient) of the univariable meta-regression line for COVID-19 prevalence was not significant for household income (P = .639), whereas the coefficient was significantly positive for black (coefficient, 0.021; P = .015), Hispanic/Latino (0.033; P < .001), and poverty (0.039; P = .02), which indicated that COVID-19 prevalence increased significantly as black, Hispanic/Latino, and poverty increased. The multivariable model revealed that the slope was significantly positive for only Hispanic/Latino ( P < .001). The coefficient in the univariable model for COVID-19 fatality, however, was not significant for all the covariate. In conclusion, black, Hispanic/Latino, and poverty (not household income), especially Hispanic/Latino independently, may be associated with COVID-19 prevalence. There may be no association of black, Hispanic/Latino, poverty, and household income with COVID-19 fatality.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.22.20110791: (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

    No key resources detected.

    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 10.1101/2020.05.22.20110791 on medRxiv