Predictive Modeling of People Movement and Disease Spread on Campus under COVID and Pandemic Situations (UA21-051)

This invention provides university policy makers a novel simulation based on a student-mobility model (a GIS map overlaid with daily student schedules including classrooms, buildings, dorms, etc.) in tandem with a disease propagation model (showing student health, shedding rate of the disease, number of infected students in various locations, probabilities of disease transmissions, etc.) so administrators can get insight into the impact of policy decisions. Background: Computer models are used in applications where the human and organizational costs are too expensive to implement in real life. It is imperative that administrators and policy makers are not ignorant to the effects of their policy decisions, nor should they be paralyzed because the effects of that paralysis may be equally deadly. Accurate models give those policy makers a reasonable glimpse of potential policy outcomes. There is a large need for these models in many areas and, in 2020, this could be the difference between locking down forever due to the COVID-19 pandemic and changing input parameters to get people back where they need to be. While there are many models considering crowd control or disease transmission, this model integrates all of the data available to the university to provide a holistic presentation of campus reactions to policy changes. Learn more at Anne Spieth 520-626-1577

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