Computational mathematics applied in the identification of the risk of indirect contagion of COVID-19 in university classrooms

Abstract

This exploratory study evaluated the risk of contagion from airborne diseases, such as coronaviruses, in schools. For three days, the concentration of carbon dioxide in two university classrooms was monitored for 90 minutes, while the students took their math classes. We use these values to validate a first-order model for carbon dioxide concentration and calculate the air exchange rate indirectly (avoiding the need for expensive measurement equipment). The air exchange rate obtained allowed us to assess whether the usual ventilation systems (both natural and mechanical) are sufficient to guarantee a low risk of contagion of aerosols due to respiration. The results show that the risk of contagion is low if three factors are considered: the level of conversation within the classroom, the usage of a moisture extraction system, and the lecture duration. The risk is low if the lecture time is less than 50 minutes, the level of conversation is moderate, and a moisture extraction system is available. If these conditions are not met the risk is considerably higher even if mechanical ventilation is employed.