Mobility-guided Modeling of the COVID-19 Pandemic in Metro Manila

  1. Bernhard Egwolf
  2. Nicanor Austriaco

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Abstract

Coronavirus disease 2019 (COVID-19) is a novel respiratory disease first identified in Wuhan, China, that is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To better understand the dynamics of the COVID-19 pandemic in the Philippines, we have used real-time mobility data to modify the DELPHI epidemiological model recently developed at the Massachusetts Institute of Technology (MIT) and to simulate the pandemic in Metro Manila. We have chosen to focus on the National Capital Region (NCR), not only because it is the nation’s demographic heart where over a tenth of the country’s population lives, but also because it has been the epidemiological epicenter of the Philippine pandemic. Our UST CoV-2 model suggests that the government-imposed enhanced community quarantine (ECQ) has successfully limited the spread of the pandemic. It is clear that the initial wave of the pandemic is flattening, though suppression of viral spread has been delayed by the local pandemics in the City of Manila and Quezon City. Our data also reveals that replacing the ECQ with a general community quarantine (GCQ) will increase the forecasted number of deaths in the nation’s capital unless rig

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  1. Version published to 10.56899/149.3a.13
  2. ScreenIT

    SciScore for 10.1101/2020.05.26.20111617: (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

    Software and Algorithms
    SentencesResources
    The function was minimized with the aid of the dual_annealing algorithm of the Python module SciPy.
    Python
    suggested: (IPython, RRID:SCR_001658)
    SciPy
    suggested: (SciPy, RRID:SCR_008058)

    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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  3. Version published to 10.1101/2020.05.26.20111617v1 on medRxiv