Monitoring carbon dioxide to quantify the risk of indoor airborne transmission of COVID-19

A new guideline for mitigating indoor airborne transmission of COVID-19 prescribes a limit on the time spent in a shared space with an infected individual (Bazant & Bush, Proceedings of the National Academy of Sciences of the United States of America, vol. 118, issue 17, 2021, e2018995118). Here, we rephrase this safety guideline in terms of occupancy time and mean exhaled carbon dioxide (CO2) concentration in an indoor space, thereby enabling the use of CO2 monitors in the risk assessment of airborne transmission of respiratory diseases. While CO2 concentration is related to airborne pathogen concentration (Rudnick & Milton, Indoor Air, vol. 13, issue 3, 2003, pp. 237-245), the guideline developed here accounts for the different physical processes affecting their evolution, such as enhanced pathogen production from vocal activity and pathogen removal via face-mask use, filtration, sedimentation and deactivation. Critically, transmission risk depends on the total infectious dose, so necessarily depends on both the pathogen concentration and exposure time. The transmission risk is also modulated by the fractions of susceptible, infected and immune people within a population, which evolve as the pandemic runs its course. A mathematical model is developed that enables a prediction of airborne transmission risk from real-time CO2 measurements. Illustrative examples of implementing our guideline are presented using data from CO2 monitoring in university classrooms and office spaces.

Automated summary

A new guideline sets a limit on time spent in shared spaces with infected individuals, and rephrases this safety guideline in terms of occupancy time and average exhaled CO2 concentration for assessing airborne transmission risk. The guideline accounts for physical processes affecting pathogen evolution and modulates transmission risk based on total infectious dose and population fractions of susceptible, infected, and immune individuals. A mathematical model is developed for predicting airborne transmission risk using real-time CO2 measurements, with illustrative examples from university classrooms and office spaces.