School Reopening Simulations with COVID-19 Agent-based Model for the Philippine Regions

  1. Vena Pearl Bongolan
  2. Nico Andrew G. Francisco
  3. Martin Thomas D. Saliba
  4. Jimuel Celeste

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Abstract

Schools have been closed in the Philippines since March 2020 due to the COVID-19 pandemic. In 2022, the government already allowed a pilot run of limited in-person classes in low-risk areas. With such development, the present paper aims to explore the question “Is it safe to reopen schools with the current vaccination coverage?” We used an age-stratified COVID-19 agent-based model coupled with social contact probabilities to simulate school reopening and vaccination scenarios in the 17 regions of the country. Through these simulations, we found downtick points for infections and deaths—the vaccination coverage at which we do not expect increases in infections and deaths should schools reopen. We then calculated the School Reopening Viability (SRV) of the regions and visualized these scores with a stop-go map for school reopening. Simulation results suggest that all regions except Regions 7, 9, BARMM, and 13 can already reopen schools without the fear of upticks in infections nor deaths. These regions have lower vaccination coverages relative to the rest of the country, especially against the case of Luzon which has the highest vaccination coverage. We recommend that the areas of concern ramp up their vaccination efforts before reopening schools. At the same time, behavioral factors (mask-wearing, physical distancing, hand-washing) and disease resistance factors (healthy living habits) shall be enforced once schools reopen. Finally, school reopening shall be gradual to ensure the crafting of data-driven (hospital utilization, positivity rate) policies.

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  1. Version published to 10.1101/2022.05.16.22275128v2 on medRxiv
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    SciScore for 10.1101/2022.05.16.22275128: (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

    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.

    Results from scite Reference Check: We found no unreliable references.

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  3. Version published to 10.1101/2022.05.16.22275128v1 on medRxiv