Influence of passenger head-position uncertainty on infection risk predictions
We investigate the influence of natural head movement on the infection risk posed by airborne pathogens using a CFD-based forward risk prediction model. Quasi-Monte-Carlo simulations are used to obtain the resulting infection risk distributions by representing head movement via probability distributions of parameters describing the position and orientation of each passenger's breathing zone. A significant impact of fore/aft and lateral head position on infection risk was found and should be accounted for to increase robustness when predictions of local, seat-specific infection risks are used to guide design and policy decisions. Unlike the sampling-based Monte Carlo approach, estimates of the statistical moments of the risk distributions and sensitivities, calculated using first-order second-moment and higher-order methods, were found to inadequately capture the dependencies between head movement components and infection risk.