  Network ecology is a rising field of quantitative biology representing
ecosystems as complex networks. A suitable example is parasite spreading:
several parasites may be transmitted among their hosts through different
mechanisms, each one giving rise to a network of interactions. Modelling these
networked, ecological interactions at the same time is still an open challenge.
We present a novel spatially-embedded multiplex network framework for modelling
multi-host infection spreading through multiple routes of transmission. Our
model is inspired by T. cruzi, a parasite transmitted by trophic and vectorial
mechanisms. Our ecological network model is represented by a multiplex in which
nodes represent species populations interacting through a food web and a
parasite contaminative layer at the same time. We modelled an SI dynamics in
two different scenarios: a simple theoretical food web and an empirical one.
Our simulations in both scenarios show that the infection is more widespread
when both the trophic and the contaminative interactions are considered with
equal rates. This indicates that trophic and contaminative transmission may
have additive effects in real ecosystems. We also find that the ratio of
vectors-to-host in the community (i) crucially influences the infection spread,
(ii) regulates a percolating phase transition in the rate of parasite
transmission and (iii) increases the infection rate in hosts. By immunising the
same fractions of predator and prey populations, we show that the multiplex
topology is fundamental in outlining the role that each host species plays in
parasite transmission in a given ecosystem. We also show that the multiplex
models provide a richer phenomenology in terms of parasite spreading dynamics
compared to mono-layer models. Our work opens new challenges and provides new
quantitative tools for modelling multi-channel spreading in networked systems.
