  Infectious diseases in livestock are well-known to infect multiple hosts and
persist through the combination of within- and between-host transmission
pathways. Uncertainty remains about the epidemic consequences of the disease
being introduced on farms with more than one susceptible host. Here we describe
multi-host contact networks to elucidate the potential of disease spread among
farms with multiple species. Four years of between-farm animal movement data of
bovine, swine, small ruminants, and multi-host, were described through both
static and time-series networks; the in-going and out-going contact chains were
also calculated. We use the proposed stochastic multilevel model to simulate
scenarios in which infection was seeded into a single host and multi-hosts
farms, to estimate epidemic trajectories and simulate network-based control
actions to assess the reduction of secondarily infected farms. Our analysis
showed that the swine network was more connected than cattle and small
ruminants in the temporal network view. The small ruminants network was shown
disconnected, however, allowing the interaction among networks with different
hosts enabling the spread of disease throughout the network. Independently from
the initial infected host, secondary infections were observed crossing overall
species. We showed that targeting the top 3.25% of the farms ranked by degree
could reduce the total number of infected farms below 70% at the end of the
simulation period. In conclusion, we demonstrated the potential of the
multi-host network in disease propagation, therefore, it becomes important to
consider the observed multi-host movement dynamics while designing surveillance
and preparedness control strategies.
