| In this dissertation, we explore the effects of fluid mechanics on airborne disease transmission in enclosed spaces. We first consider transmissibility in rooms where the air is approximated as well mixed. We present a model for assessing risk using fundamental conservation principles. This versatile technique allows for the prediction of transmission probabilities for transient scenarios, where parameters such as the pathogen growth kinetics within the infector or the fresh air ventilation rate are varying with time. We then relax the assumption of perfect mixing by incorporating a residence time distribution into the model. Our findings demonstrate the importance of considering realistic mixing conditions, and we show that the use of the perfect mixing assumption leads to a significant underestimate of the infection risk during transient exposures.;We then turn our attention to situations where the air is not well mixed. Specifically, we develop a model to assess airborne transmission risk in animal experiments, where there is a directional airflow transporting pathogen-laden particles from an inoculated animal downstream towards an exposed animal. We consider all aspects of transmission, from growth of the pathogen in the source animal to infection in the naive animal. Our work illustrates the large effect that both the fluid mechanics and pathogen growth kinetics play on the likelihood of new infection. The model suggests that the turbulent dispersivity is a key input, so we then present experimental measurements for this parameter under conditions similar to those used for animal transmission experiments. Our results indicate that the dispersivity is counterintuitively unaffected by the fan speed but is sensitive to the fan shape, a finding that simplifies disease transmission modeling. Finally, we conclude by presenting areas for future work in airborne disease transmission modeling. |
