Systems and methods for predictive modeling of people movement and disease spread under covid and pandemic situations

Abstract

Systems and methods are described for agent-based simulation of each individual's movements in order to monitor the propagation of a disease. An agent-based simulation model has been exemplarily constructed, which is mainly comprised of two parts: student mobility model and disease propagation model. In the student mobility model, movements of students are modeled based on the GIS map (viz. routes, distances) and their daily schedules (e.g. dorms and classrooms/buildings). The disease propagation model represents students' health status (viz. susceptible, pre-symptomatic, asymptomatic, quarantine, isolation, and recovered) based on different factors such as the number of infected students attending the class or living in a dorm, classroom/dorm features (e.g. size, humidity, ventilation), probabilities of disease transmissions (e.g. droplet, airborne) in classrooms based on a dose-response model, probabilities of disease transmissions in dorms based on cohort studies, and mask wearing condition and effectiveness.

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