Effects of social structure and management on risk of disease establishment in wild pigs

1. Contact heterogeneity among hosts determines invasion and spreading
dynamics of infectious disease, thus its characterization is essential for
identifying effective disease control strategies. Yet, little is known
about the factors shaping contact networks in many wildlife species and
how wildlife management actions might affect contact networks. 2. Wild
pigs in North America are an invasive, socially-structured species that
pose a health concern for domestic swine given their ability to transmit
numerous devastating diseases such as African swine fever (ASF). Using
proximity loggers and GPS data from 48 wild pigs in Florida and South
Carolina, USA, we employed a probabilistic framework to estimate weighted
contact networks. We determined the effects of sex, social group, and
spatial distribution (monthly home range overlap and distance) on wild pig
contact. We also estimated the impacts of management-induced perturbations
on contact and inferred their effects on ASF establishment in wild pigs
with simulation. 3. Social group membership was the primary factor
influencing contacts. Between-group contacts depended primarily on space
use characteristics, with fewer contacts among groups separated by
>2 km and no contacts among groups >4 km apart within a
month. 4. Modeling ASF dynamics on the contact network demonstrated that
indirect contacts resulting from baiting (a typical method of attracting
wild pigs or game species to a site to enhance recreational hunting)
increased the risk of disease establishment by ~33% relative to direct
contact. Low-intensity population reduction (<5.9% of the
population) had no detectable impact on contact structure but reduced
predicted ASF establishment risk relative to no population reduction. 5.
We demonstrate an approach for understanding the relative role of spatial,
social, and individual-level characteristics in shaping contact networks
and predicting their effects on disease establishment risk, thus providing
insight for optimizing disease control in spatially- and
socially-structured wildlife species.