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Exploring a targeted approach for public health capacity restrictions during COVID-19 using a new computational model
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作者 Ashley N.Micuda Mark R.Anderson +11 位作者 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 《Infectious Disease Modelling》 CSCD 2024年第1期234-244,共11页
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 t... 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. 展开更多
关键词 Monte-carlo Agent-based epidemic modelling COVID-19 Small business capacity restrictions Public health Basic reproductive number
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