This is a tool to help understand COVID-19 transmission risk to students and teachers/professors due to transmission by microscopic airborne particles (i.e. aerosols) in classroom settings. This is not an infectious disease dynamics model, but rather a model that predicts airborne virion concentrations within a classroom, taking into account exhalation of virion-containing aerosols by infected individuals and the loss of these particles due to various processes. Probabilities of infection are calculated based on the virion dose inhaled (accounting for use of masks) by uninfected people in the classroom.
The risk calculations here are only for disease transmission by the airborne aerosol route, and do not account for transmission by droplets or from contaminated surfaces. The implicit assumption is that appropriate social distancing and hygiene protocols are strictly adhered to in the classroom. To the extent that this is not true, the risk of infection will be higher than predicted by these calculations. Users should also also bear in mind that the absolute estimates of predicted risk from this model are quite uncertain because of uncertainties in our knowledge of key parameters such as the exhalation rate of virion-containing aerosols by infected individuals and the percentage of infected individuals in the classroom. The model is nevertheless useful to explore the relative effects of control measures (e.g. more ventilation, fewer people, shorter duration, masks vs no masks) on COVID-19 transmission by aerosols in classrooms.
This probabilistic Monte Carlo framework was developed by Prasad Kasibhatla, as an offshoot of the COVID-19 risk estimator developed by Jose Jimenez.
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