文章基本信息

标题：3D Agent-Based Model of Pedestrian Movements for Simulating COVID-19 Transmission in University Students
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作者：David Alvarez Castro ; Alistair Ford
期刊名称：ISPRS International Journal of Geo-Information
电子版ISSN：2220-9964
出版年度：2021
卷号：10
期号：8
页码：509
DOI：10.3390/ijgi10080509
语种：English
出版社：MDPI AG
摘要：On the 30 January 2020, the WHO declared a public health emergency of international concern due to the coronavirus disease 2019 (COVID-19). Social restrictions with different efficiencies were put in place to avoid transmission. Students living in student accommodation constitute an interesting group to test restrictions because they share living places, workplaces and daily routines, which are key factors in the transmission. In this paper, we present a new geospatial agent-based simulation model to explore the transmission of COVID-19 between students living in Newcastle University accommodation and the efficiency of simulated restrictions (e.g., facemask, lockdown, self-isolation). Results showed that facemasks could reduce infection peak by 30% if worn by all students; an early lockdown could keep 65% of the students safe in the best case; self-isolation could keep 86% of the students safe; while the combination of these measures could prevent disease in 95% of students in the best case-scenario. Spatial analyses showed that the most dangerous places were those where many students interact for a long time, such as faculties and accommodation. The developed ABM could help university managers to respond to current and future epidemics and plan effective responses to keep safe as many students as possible.