  In the case of airborne diseases, pathogen copies are transmitted by droplets
of respiratory tract fluid that are exhaled by the infectious and, after
partial or full drying, inhaled as aerosols by the susceptible. The risk of
infection in indoor environments is typically modelled using the Wells-Riley
model or a Wells-Riley-like formulation, usually assuming the pathogen dose
follows a Poisson distribution (mono-pathogen assumption). Aerosols that hold
more than one pathogen copy, i.e. poly-pathogen aerosols, break this assumption
even if the aerosol dose itself follows a Poisson distribution. For the largest
aerosols where the number of pathogen in each aerosol can sometimes be several
hundred or several thousand, the effect is non-negligible, especially in
diseases where the risk of infection per pathogen is high. Here we report on a
generalization of the Wells-Riley model and dose-response models for
poly-pathogen aerosols by separately modeling each number of pathogen copies
per aerosol, while the aerosol dose itself follows a Poisson distribution. This
results in a model for computational risk assessment suitable for
mono-/poly-pathogen aerosols. We show that the mono-pathogen assumption
significantly overestimates the risk of infection for high pathogen
concentrations in the respiratory tract fluid. The model also includes the
aerosol removal due to filtering by the individuals which becomes significant
for poorly ventilated environments with a high density of individuals, and
systematically includes the effects of facemasks in the infectious aerosol
source and sink terms and dose calculations.
