Using contact networks to explore mechanisms of parasite transmission in wildlife.

A hallmark assumption of traditional approaches to disease modelling is that individuals within a given population mix uniformly and at random. However, this assumption does not always hold true; contact heterogeneity or preferential associations can have a substantial impact on the duration, size, and dynamics of epidemics. Contact heterogeneity has been readily adopted in epidemiological studies of humans, but has been less studied in wildlife. While contact network studies are becoming more common for wildlife, their methodologies, fundamental assumptions, host species, and parasites vary widely. The goal of this article is to review how contact networks have been used to study macro- and microparasite transmission in wildlife. The review will: (i) explain why contact heterogeneity is relevant for wildlife populations; (ii) explore theoretical and applied questions that contact networks have been used to answer; (iii) give an overview of unresolved methodological issues; and (iv) suggest improvements and future directions for contact network studies in wildlife.

Infectious disease transmission and contact networks in wildlife and livestock.

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.