摘要
This work introduces the Queen's University Agent-Based Outbreak Outcome Model(QUABOOM).This tool is an agent-based Monte Carlo simulation for modelling epidemics and informing public health policy.We illustrate the use of the model by examining capacity restrictions during a lockdown.We find that public health measures should focus on the few locations where many people interact,such as grocery stores,rather than the many locations where few people interact,such as small businesses.We also discuss a case where the results of the simulation can be scaled to larger population sizes,thereby improving computational efficiency.
基金
support of the Department of Physics,Engineering Physics&Astronomy at Queen's University through a research initiation grant,the Queen's University Arts and Science Research Fund
the Queen's University Bartlett Student Initiatives Fund
the Natural Sciences and Engineering Research Council of Canada,funding reference number SAPIN-2017-00023.
