Prevention of SARS-CoV-2 airborne transmission in a workplace based on CO2 sensor network

We measured the compartmental air change per hour (ACH) using a CO2 sensor network in an office space where a cluster of COVID-19 infections attributed to aerosol transmission occurred. Generalized linear mixed models and dynamic time warping were used for a time series data analysis, and the results indicated that the ventilation conditions were poor at the time of the cluster outbreak, and that the low ACH in the room likely contributed to the outbreak. In addition, the adverse effects of inappropriate partitions and the effectiveness of ventilation improvements were investigated in detail. ACH of less than 2 /h was considered a main contributor for the formation of the COVID-19 cluster in the studied facility. Practical ImplicationsA systematic method for measuring and evaluating indoor ventilation to prevent the spread of infectious diseases caused by aerosols is presented. Ventilation bias caused by ventilation pathways and inappropriate use of plastic sheeting can be detected by a CO2 sensor network and time series data analysis. Estimated ventilation rate will be a good index to suppress the formation of the COVID-19 cluster.