  African swine fever (ASF) is a highly virulent viral disease that affects
both domestic pigs and wild boar. Current ASF transmission in Europe is in part
driven by wild boar populations, which act as a disease reservoir. Wild boar
are abundant throughout Europe and are highly social animals with complex
social organisation. Despite the known importance of wild boar in ASF spread
and persistence, there remain knowledge gaps surrounding wild boar
transmission. To investigate the influence of density-contact functions and
wild boar social structure on disease dynamics, we developed a wild boar
modelling framework. The framework included an ordinary differential equation
model, a homogeneous stochastic model, and various network-based stochastic
models that explicitly included wild boar social grouping. We found that power
law functions (transmission $\propto$ density$^{0.5}$) and frequency-based
density-contact functions were best able to reproduce recent Baltic outbreaks;
however, power law function models predicted considerable carcass transmission,
while frequency-based models had negligible carcass transmission. Furthermore,
increased model heterogeneity caused a decrease in the relative importance of
carcass-based transmission. The different dominant transmission pathways
predicted by each model type affected the efficacy of potential interventions,
which highlights the importance of evaluating model type and structure when
modelling systems with uncertainties.
