Integrating ecology and epidemiology using individual-based multi-species networks
- Published
- Accepted
- Subject Areas
- Computational Biology, Ecology, Epidemiology
- Keywords
- networks, ecology, epidemiology, diseae, host-parasite interactions, individual traits
- Copyright
- © 2014 Pilosof et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2014. Integrating ecology and epidemiology using individual-based multi-species networks. PeerJ PrePrints 2:e307v1 https://doi.org/10.7287/peerj.preprints.307v1
Abstract
Parasite transmission in host communities is a function of ecological factors that influence interspecific contacts and contact patterns within species. These two levels are studied with different kinds of networks – ecological networks and individual contact networks – and the integration of these levels is essential for effective understanding of parasite transmission. We combined these approaches by creating epidemiological networks based on parasite sharing from individual-based ecological host-parasite networks. We compared multi- to single-species networks to investigate the drivers of helminth infection in wild individual rodents of South-east Asia. Network modularity was higher in the multi-species than in the single-species networks. Phylogeny affected affiliation of individuals to modules. The importance of individuals differed between multi- and single-species networks, with species identity and individual traits influencing their position in the networks. Simulations revealed that a novel parasite spreads more slowly in multi- than in single-species networks and that this depended on network structure. Although the relative contribution of within- vs. between-species transmission rates to disease dynamics is important, using multi-host epidemiological networks improves our understanding of parasite dynamics as it further considers interaction structure between individuals.