[论文解读] How to restart? An agent-based simulation model towards the definition of strategies for COVID-19 "second phase" in public buildings

Marco D’Orazio, Gabriele Bernardini+1 more|arXiv (Cornell University)|Apr 27, 2020

COVID-19 epidemiological studies参考文献 51被引用 39

一句话总结

一种基于代理的模型，用于评估在COVID-19期间重新开放公共建筑的策略，聚焦口罩使用、容量限制和进入控制，以 Diamond Princess 数据进行标定，并应用于大学校园区域。

ABSTRACT

Restarting public buildings activities in the "second phase" of COVID-19 emergency should be supported by operational measures to avoid a second virus spreading. Buildings hosting the continuous presence of the same users and significant overcrowd conditions over space/time (e.g. large offices, universities) are critical scenarios due to the prolonged contact with infectors. Beside individual's risk-mitigation strategies performed (facial masks), stakeholders should promote additional strategies, i.e. occupants' load limitation (towards "social distancing") and access control. Simulators could support the measures effectiveness evaluation. This work provides an Agent-Based Model to estimate the virus spreading in the closed built environment. The model adopts a probabilistic approach to jointly simulate occupants' movement and virus transmission according to proximity-based and exposure-time-based rules proposed by international health organizations. Scenarios can be defined in terms of building occupancy, mitigation strategies and virus-related aspects. The model is calibrated on experimental data ("Diamond Princess" cruise) and then applied to a relevant case-study (a part of a university campus). Results demonstrate the model capabilities. Concerning the case-study, adopting facial masks seems to be a paramount strategy to reduce virus spreading in each initial condition, by maintaining an acceptable infected people's number. The building capacity limitation could support such measure by potentially moving from FFPk masks to surgical masks use by occupants (thus improving users' comfort issues). A preliminary model to combine acceptable mask filters-occupants' density combination is proposed. The model could be modified to consider other recurring scenarios in other public buildings (e.g. tourist facilities, cultural buildings).

研究动机与目标

• 让在持续占用和可能过度拥挤的建筑中推动采取运营措施，避免第二波疫情。
• 开发一个代理模型，模拟在基于邻近性和暴露时间规则下的移动和病毒传播。
• 用实验数据（Diamond Princess）对模型进行标定，并将其应用到一个真实的大学校园案例研究。
• 评估口罩、容量限制和进入控制策略对感染传播的影响。

提出的方法

• 构建一个代理模型，联合模拟占用者的移动和病毒传播。
• 实现基于近距离和基于暴露时间传播的概率规则，灵感来自国际卫生指南。
• 通过改变建筑物占用、缓解策略和病毒相关参数来定义情景。
• 使用 Diamond Princess 数据进行标定，并在大学校园案例研究中进行验证。
• 提供一种将口罩过滤效力与 occupant 密度相结合的初步方法。

实验结果

研究问题

• RQ1 在长期占用的公共建筑中，容量限制和进入控制措施如何影响COVID-19扩散？
• RQ2 在建模环境中，不同口罩类型和密度对感染动态的相对影响如何？
• RQ3 当以 Diamond Princess 数据进行标定并应用于大学校园情景时，模型能否再现观察到的传播模式？

主要发现

• 口罩使用似乎是在初始条件下减少传播的首要策略。
• 容量限制可以通过允许从高过滤（FFPk）口罩向医用口罩/外科口罩的过渡来支持佩戴口罩。
• 初步模型表明口罩有效性与占用密度的可行组合可在减轻感染方面发挥作用。
• 该框架可以适用于案例研究以外的其他公共建筑。