Exploring a targeted approach for public health capacity restrictions during COVID-19 using a new computational model

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. (c) 2024 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).