Dezembro 2020 vol. 8 num. 4 - XXIV International Conference of the Iberoamerican Society of Digital Graphics

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Spatiotemporal Modeling of COVID-19 Spread in Built Environments

Spatiotemporal Modeling of COVID-19 Spread in Built Environments

Gomez, Paula ; Hadi, Khatereh ; Kemenova, Olga ; Swarts, Matthew ;

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This research proposes a Spatiotemporal Modeling approach to understand the role of architecture, specifically the built environment, in the COVID-19 pandemic. The model integrates spatial and temporal parameters to calculate the probability of spread of and exposure to SARS-CoV-2 virus (responsible of COVID-19 disease) due to the combination of four aspects: Spatial configuration, organizational schedules, people’s behavior, and virus characteristics. Spatiotemporal Modeling builds upon the current models of building analytics for architecture combined with predictive models of COVID-19 spread. While most of the current research on COVID-19 spread focuses on mathematical models at regional scales and the CDC guidelines emphasizing on human behavior, our research focuses on the role of buildings in this pandemic, as the intermediate mechanism where human and social activities occur. The goal is to understand the most significant parameters that influence the virus spread within built environments, including human-to-human, fomite (surface-to-human), and airborne ways of transmission, with the purpose of providing a comprehensive parametric model that may help identify the most influential design and organizational decisions for controlling the pandemic. The proof-of-concept study is a healthcare facility.

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Palavras-chave: Spatiotemporal modeling, Agent-based simulation, COVID-19, Virus spread, Built environments, Human behavior, Social distancing,

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DOI: 10.5151/sigradi2020-134

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Como citar:

Gomez, Paula; Hadi, Khatereh; Kemenova, Olga; Swarts, Matthew; "Spatiotemporal Modeling of COVID-19 Spread in Built Environments", p. 991-996 . In: Congreso SIGraDi 2020. São Paulo: Blucher, 2020.
ISSN 2318-6968, DOI 10.5151/sigradi2020-134

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