During the COVID-19 pandemic, implementing in-person indoor instruction in a safe manner was a high priority for universities nationwide. To support this effort at the University, we developed a mathematical model for estimating the risk of SARS-CoV-2 transmission in university classrooms. This model was used to design a safe classroom environment at the University during the COVID-19 pandemic that supported the higher occupancy levels needed to match pre-pandemic numbers of in-person courses, despite a limited number of large classrooms. A retrospective analysis at the end of the semester confirmed the model's assessment that the proposed classroom configuration would be safe. Our framework is generalizable and was also used to support reopening decisions at Stanford University. In addition, our methods are flexible; our modeling framework was repurposed to plan for large university events and gatherings. We found that our approach and methods work in a wide range of indoor settings and could be used to support reopening planning across various industries, from secondary schools to movie theaters and restaurants.

翻译：在COVID-19疫情期间，如何以安全方式开展室内面授教学是美国各大学的首要任务。为支持本校的此项工作，我们开发了一个用于估算大学教室中SARS-CoV-2传播风险的数学模型。该模型被用于设计疫情期间大学的安全教室环境，在大型教室数量有限的情况下支持了更高的人员密度，以满足疫情前面授课程的数量需求。学期末的回顾性分析证实了该模型关于所提议教室配置安全性的评估结论。我们的框架具有通用性，并已被用于支持斯坦福大学的复课决策。此外，我们的方法具有灵活性：该建模框架被重新调整用于规划大型大学活动和集会。我们发现，我们的方法适用于广泛的室内环境，可支持从中学到电影院和餐厅等各类场所的复课规划。