Ashley N. Micuda , Mark R. Anderson , Irina Babayan , Erin Bolger , Logan Cantin , Gillian Groth , Ry Pressman-Cyna , Charlotte Z. Reed , Noah J. Rowe , Mehdi Shafiee , Benjamin Tam , Marie C. Vidal , Tianai Ye , Ryan D. Martin
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引用次数: 0
Abstract
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.
期刊介绍：
Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.
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