Graz University of Technology, Institute for Interactive Systems and Data Science, Graz, Austria.
Complexity Science Hub Vienna, Vienna, Austria.
Clin Infect Dis. 2022 Dec 19;75(12):2097-2103. doi: 10.1093/cid/ciac340.
Returning universities to full on-campus operations while the coronavirus disease 2019 pandemic is ongoing has been a controversial discussion in many countries. The risk of large outbreaks in dense course settings is contrasted by the benefits of in-person teaching. Transmission risk depends on a range of parameters, such as vaccination coverage and efficacy, number of contacts, and adoption of nonpharmaceutical intervention measures. Owing to the generalized academic freedom in Europe, many universities are asked to autonomously decide on and implement intervention measures and regulate on-campus operations. In the context of rapidly changing vaccination coverage and parameters of the virus, universities often lack sufficient scientific insight on which to base these decisions.
To address this problem, we analyzed a calibrated, data-driven agent-based simulation of transmission dynamics among 13 284 students and 1482 faculty members in a medium-sized European university. Wed use a colocation network reconstructed from student enrollment data and calibrate transmission risk based on outbreak size distributions in education institutions. We focused on actionable interventions that are part of the already existing decision process of universities to provide guidance for concrete policy decisions.
Here we show that, with the Omicron variant of the severe acute respiratory syndrome coronavirus 2, even a reduction to 25% occupancy and universal mask mandates are not enough to prevent large outbreaks, given the vaccination coverage of about 85% reported for students in Austria.
Our results show that controlling the spread of the virus with available vaccines in combination with nonpharmaceutical intervention measures is not feasible in the university setting if presence of students and faculty on campus is required.
在 2019 冠状病毒病大流行期间，让大学全面恢复面授课程是许多国家颇具争议的讨论话题。在密集课程环境中发生大规模疫情的风险与面对面教学的益处形成对比。传播风险取决于一系列参数，例如疫苗接种覆盖率和效力、接触者人数以及非药物干预措施的采用。由于欧洲普遍存在学术自由，许多大学被要求自主决定并实施干预措施以及规范校园运作。在疫苗接种覆盖率和病毒参数迅速变化的情况下，大学往往缺乏足够的科学依据来做出这些决策。
为了解决这个问题，我们分析了对 13284 名学生和 1482 名教职员工在一所中等规模欧洲大学中传播动态的校准、数据驱动的基于代理的模拟。我们使用了从学生注册数据重建的共置网络，并根据教育机构中疫情规模分布来校准传播风险。我们专注于可采取的干预措施，这些措施是大学已经存在的决策过程的一部分，旨在为具体的政策决策提供指导。
在这里，我们表明，考虑到奥地利学生报告的约 85%的疫苗接种覆盖率，即使 occupancy 降低到 25%且普遍要求戴口罩，鉴于严重急性呼吸综合征冠状病毒 2 的奥密克戎变体，也不足以防止大规模疫情。
我们的结果表明，如果需要学生和教职员工在校，那么在大学环境中，利用现有疫苗结合非药物干预措施控制病毒传播是不可行的。
