Transmission of Respiratory Infectious Diseases between Neighboring Cities using Agent-based Model and Compartmental Model

  1. Christian Alvin H. Buhat
  2. Destiny SM. Lutero
  3. Yancee H. Olave
  4. Monica C. Torres
  5. Jomar F. Rabajante

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Abstract

We formulate an agent-based model and a compartmental model (SEIR) that simulate the spread of a respiratory infectious disease between two neighboring cities. We consider preventive measures such as implementation of social distancing and lockdown in a city, as well as the effect of protective gears or practices. The chance of travelling to another city and within the city during lockdown, and initial percentage of exposed and infected individuals on both cities influence the increase in the number of newly-infected individuals on both models. Our simulations show that (i) increase in exposed individuals results in increase in number of new infections, hence the need for increased testing-isolation efforts; (ii) protection level of 75-100% effectiveness impedes disease transmission; (iii) travelling within city or to other city can be an option given that strict preventive measures (e.g., non-pharmaceutical interventions) are observed; and (iv) the ideal set-up for neighboring cities is to implement lockdown when there is high risk of disease local transmission while individuals observe social distancing, maximizing protective measures, and isolating those that are exposed. The results of the agent-based and compartmental models show similar qualitative dynamics; the differences are due to different spatio-temporal heterogeneity and stochasticity. These models can aid decision makers in designing infectious disease-related policies to protect individuals while continuing population movement.

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    SciScore for 10.1101/2020.06.24.20138818: (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: Thank you for sharing your code and data.

    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.

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    Results from JetFighter: We did not find any issues relating to colormaps.

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    • 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 10.1101/2020.06.24.20138818v1 on medRxiv