Due to the increasing amount of time that people are spending indoors, the need to ensure adequate ventilation has become a priority. The confirmed airborne transmission of COVID-19 highlights the necessity to consider the effect of ventilation on the reduction of the infection risk. In naturally ventilated buildings, the ventilation rate is not easy to determine, and it is difficult to estimate the risk to implement preventive measures. This paper presents a method to estimate the infection probability from CO₂ concentration monitoring, which was applied to university classrooms. The effects of people’s activity, classroom characteristics, occupancy and protective masks were also investigated. From the method, it is possible to calculate the infection probability using CO₂ dataloggers that can be adopted as ‘alarm’ systems to keep the infection probability below a critical value. The method will enhance healthy conditions indoors and reduce the risk of infectious diseases in the future.

由于人们在室内度过的时间越来越多，因此确保足够的通风已成为当务之急。已确认的 COVID-19 空气传播强调了考虑通风对降低感染风险的影响的必要性。在自然通风的建筑物中，通风率不易确定，难以估计实施预防措施的风险。本文提出了一种通过 CO ₂浓度监测来估计感染概率的方法，该方法应用于大学课堂。还调查了人们的活动、教室特征、占用率和防护口罩的影响。根据该方法，可以使用 CO _{2计算感染概率}可以用作“警报”系统的数据记录器，以将感染概率保持在临界值以下。该方法将改善室内健康状况，并降低未来感染传染病的风险。