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.

Healthcare design practice has shown increasing interest in the assessment of design alternatives from a human-centered approach, focusing on organizational performance, patient health, and wellness outcomes, in addition to building performance. The goal of this research is to advance building analytics by identifying, defining and implementing computational human-centered design metrics. The knowledge is extracted from an exhaustive literature review in the field of evidence-based design (EBD), which has studied the associations between building features and the occupants' outcomes but has not yet consolidated the findings into metrics and implications for design practice in a systematic manner. In consultation with industry experts, we have prioritized the evaluation aspects and developed a weighted evaluation framework for assessment of various design options. The developed metrics that input building parameters and output potential health and performance outcomes are implemented in a a parametric environment utilizing add-ons accordingly, and using an ambulatory clinic designed by Perkins&Will as a case study.

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