A novel demographic-based model shows that intensive testing and social distancing are concurrently required to extinguish COVID-19 progression in densely populated urban areas

  1. Mario Moisés Alvarez
  2. Grissel Trujillo-de Santiago

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Abstract

We present a simple epidemiological model that includes demographic density, social distancing, and efficacy of massive testing and quarantine as the main parameters to model the progression of COVID-19 pandemics in densely populated urban areas (i.e., above 5,000 inhabitants km 2 ). Our model demonstrates that effective containment of pandemic progression in densely populated cities is achieved only by combining social distancing and widespread testing for quarantining of infected subjects. Our results suggest that extreme social distancing without intensive testing is ineffective in extinguishing COVID-19. This finding has profound epidemiological significance and sheds light on the controversy regarding the relative effectiveness of widespread testing and social distancing. Our simple epidemiological simulator is also useful for assessing the efficacy of governmental/societal responses to an outbreak.

This study also has relevant implications for the concept of smart cities, as densely populated areas are hotspots that are highly vulnerable to epidemic crises.

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  1. Version published to 10.1101/2020.06.23.20138743v3 on medRxiv
  2. Version published to 10.1101/2020.06.23.20138743v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2020.06.23.20138743: (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: Please consider improving the rainbow (“jet”) colormap(s) used on pages 32 and 31. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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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  4. Version published to 10.1101/2020.06.23.20138743v1 on medRxiv