标题： 评估耦合空间-SIR 基于代理的模拟框架对室内非药物干预措施在应对 COVID-19 流行中的效果 显示英文标题

标题： Evaluating Efficacy of Indoor Non-Pharmaceutical Interventions against COVID-19 Outbreaks with a Coupled Spatial-SIR Agent-Based Simulation Framework

摘要： 接触性呼吸道疾病，如新冠状病毒病，依赖于足够长的接触时间才能成功传播病原体。 对于组织来说，评估旨在减轻其员工之间病毒传播的干预措施的有效性非常重要。 我们开发了一个操作风险评估模拟框架，将空间代理模型与SIR流行病学模型相结合，以评估不同干预策略的相对风险。 通过在麻省理工学院的STATA大楼应用我们的模型，我们评估了三种可能的干预维度的影响：单向移动与无限制移动、现场允许的人口数量以及离开指定工作地点休息的频率。 我们发现，单向移动限制对无限制移动没有显著影响。 相反，我们发现，将进入人数降低到当前建议以下，并建议个人减少离开工作站的频率，可以降低接触网络中高度连接个体的可能性，从而降低总体感染风险。 我们根据其流行病学效果发现了三类可能的干预措施。 通过假设二次攻击率数据与SIR模型中的传染性之间存在直接关系，我们在模拟区域内比较了四种呼吸道疾病（中东呼吸综合征、严重急性呼吸综合征、新冠状病毒病和麻疹）的相对感染风险，并推荐了适当的干预指南。 显示英文摘要

摘要： Contagious respiratory diseases, such as COVID-19, depend on sufficiently prolonged exposures for the successful transmission of the underlying pathogen. It is important for organizations to evaluate the efficacy of interventions aiming at mitigating viral transmission among their personnel. We have developed a operational risk assessment simulation framework that couples a spatial agent-based model of movement with a SIR epidemiological model to assess the relative risks of different intervention strategies. By applying our model on MIT's STATA building, we assess the impacts of three possible dimensions of intervention: one-way vs unrestricted movement, population size allowed onsite, and frequency of leaving designated work location for breaks. We find that there is no significant impact made by one-way movement restrictions over unrestricted movement. Instead, we find that a combination of lowering the number of individuals admitted below the current recommendations and advising individuals to reduce the frequency at which they leave their workstations lowers the likelihood of highly connected individuals within the contact networks that emerge, which in turn lowers the overall risk of infection. We discover three classes of possible interventions based on their epidemiological effects. By assuming a direct relationship between data on secondary attack rates and transmissibility in the SIR model, we compare relative infection risk of four respiratory diseases, MERS, SARS, COVID-19, and Measles, within the simulated area, and recommend appropriate intervention guidelines.