The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools.

1 Knowledge of infection reservoir dynamics is critical for effective disease control, but identifying reservoirs of multi-host pathogens is challenging. Here, we synthesize several lines of evidence to investigate rabies reservoirs in complex carnivore communities of the Serengeti ecological region in northwest Tanzania, where the disease has been confirmed in 12 carnivore species. 2 Long-term monitoring data suggest that rabies persists in high-density domestic dog Canis familiaris populations (> 11 dogs km⁻²) and occurs less frequently in lower-density (< 5 dogs km⁻²) populations and only sporadically in wild carnivores. 3 Genetic data show that a single rabies virus variant belonging to the group of southern Africa canid-associated viruses (Africa 1b) circulates among a range of species, with no evidence of species-specific virus–host associations. 4 Within-species transmission was more frequently inferred from high-resolution epidemiological data than between-species transmission. Incidence patterns indicate that spill-over of rabies from domestic dog populations sometimes initiates short-lived chains of transmission in other carnivores. 5 Synthesis and applications. The balance of evidence suggests that the reservoir of rabies in the Serengeti ecosystem is a complex multi-host community where domestic dogs are the only population essential for persistence, although other carnivores contribute to the reservoir as non-maintenance populations. Control programmes that target domestic dog populations should therefore have the greatest impact on reducing the risk of infection in all other species including humans, livestock and endangered wildlife populations, but transmission in other species may increase the level of vaccination coverage in domestic dog populations necessary to eliminate rabies.

Territoriality in animal populations creates spatial structure that is thought to naturally buffer disease invasion. Often, however, territorial populations also include highly mobile, non-residential individuals that potentially serve as disease superspreaders. Using long-term data from the Serengeti Lion Project, we characterize the contact network structure of a territorial wildlife population and address the epidemiological impact of nomadic individuals. As expected, pride contacts are dominated by interactions with neighbouring prides and interspersed by encounters with nomads as they wander throughout the ecosystem. Yet the pride–pride network also includes occasional long-range contacts between prides, making it surprisingly small world and vulnerable to epidemics, even without nomads. While nomads increase both the local and global connectivity of the network, their epidemiological impact is marginal, particularly for diseases with short infectious periods like canine distemper virus. Thus, territoriality in Serengeti lions may be less protective and non-residents less important for disease transmission than previously considered.

Although the approach of contact network epidemiology has been increasing in popularity for studying transmission of infectious diseases in human populations, it has generally been an underutilized approach for investigating disease outbreaks in wildlife populations. In this paper we explore the differences between the type of data that can be collected on human and wildlife populations, provide an update on recent advances that have been made in wildlife epidemiology by using a network approach, and discuss why networks might have been underutilized and why networks could and should be used more in the future. We conclude with ideas for future directions and a call for field biologists and network modelers to engage in more cross-disciplinary collaboration.

Significance: Understanding how emerging infectious and zoonotic diseases spread through space and time is critical for predicting outbreaks and designing interventions; disease models are important tools for realizing these goals. Currently, humans are altering the environment in unprecedented ways through urbanization, habitat fragmentation, and climate change. However, the consequences of increasingly heterogeneous landscapes on pathogen transmission and persistence remain unclear. By synthesizing mathematical modeling and movement ecology approaches, we examined how wildlife movement patterns interact with broad-scale landscape structure to affect population-level disease dynamics. We found that habitat fragmentation could counterintuitively promote disease outbreaks but that, for higher wildlife densities and longer infectious periods, small differences in how hosts navigated their environments could dramatically alter observed disease dynamics.