Neighborhood-Level Public Facilities and COVID-19 Transmission: A Nationwide Geospatial Study In China

  1. Xurui Jin
  2. Yu Leng
  3. Enying Gong
  4. Shangzhi Xiong
  5. Yao Yao
  6. Rajesh Vedanthan
  7. Chenkai Wu
  8. Lijing L. Yan

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Abstract

Individual-level studies on the coronavirus disease 2019 (COVID-19) have proliferated; however, research on neighborhood-level factors associated with COVID-19 is limited. We gathered the geographic data of all publically released COVID-19 cases in China and used a case-control (1:4 ratio) design to investigate the association between having COVID-19 cases in a neighborhood and number and types of public facilities nearby. Having more restaurants, shopping centers, hotels, living facilities, recreational facilities, public transits, educational institutions, and health service facilities was associated with significantly higher odds of having COVID-19 cases in a neighborhood. The associations for restaurants, hotels, reactional and education facilities were more pronounced in cities with fewer than six million people than those in larger cities. Our results have implications for designing targeted prevention strategies at the neighborhood level to reduce the burden of COVID-19.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.25.20181362: (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.

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  2. Version published to 10.1101/2020.08.25.20181362v1 on medRxiv