Development and Application of a Computational Model to Predict Fugitive Emissions during Nebuliser Therapy

Nebuliser therapy is widely used to treat respiratory diseases in clinical and homecare settings. However, this approach poses a risk of emitting fugitive medical aerosol, potentially affecting healthcare workers and bystanders. In-vitro nebulisation data using Approximate Bayesian Computation were employed to determine model parameterisation values to capture emission rates for different patient interface combinations. The model simulated aerosol concentrations and estimated inhalation exposure in different homecare settings and ventilation conditions. This novel model predicts aerosol concentrations and recommends increasing ventilation during respiratory therapy to minimise inhalation exposure. Overall, these research findings will provide vital data to better understand the exposure of occupational and homecare workers to nebuliser medical aerosol in different settings and aid in developing appropriate mitigation measures.