bioRxivEcologyPreprint
Using social network analysis and non-invasive antibody detection to explore pathogen exposure in wildlife communities
Oriane PloquiniD, Oriane BassoiD, Mthabisi Ndlovu, Franck PrugnolleiD, Alexandre CaroniD, Martin Munzamba, Emildah Porovha, Khanyile Nkomo, Gaëlle Corbel, Céline ArnathauiD, Anne BoissièreiD, Valérie PinarelloiD, Nina RaultiD, Richard Shumba, Masotsha Mhlanga, Tawanda TarakiniiD, Simon Chamaillé‐JammesiD, Hervé FritziD, Florian LiégeoisiD, Ellen Mwandirigana, Constance Sibelo, Chaitezvi Columbus, Hillary Madzikanda, Vladimir GrosboisiD, Eve MigueliD
Abstract
Understanding the dynamics of infectious diseases in ecosystems shared with wildlife is a priority for preventing future threats to human, animal health and conservation. However, the collection of ecological and epidemiological data on wild populations has relied on invasive and costly methods which limited the capacity of investigation. Recent technological developments have changed this trend. In Hwange national park and its surrounding area in Zimbabwe, we combined camera trap-based ecological monitoring over a period of 12 months, covering 14 water holes with a fecal-based antibody survey in 16 large herbivore species. A survey involving 52,829 pictures as well as 629 faecal samples collected every 15 days, has shown Through the modelling of multispecies contact networks, the risk of infection exposure at species-level is predicted. Coupled with foot-and-mouth disease virus (FMDV) antibody information, the role of each species in the dynamics of infectious diseases is explored. This study highlights how community networks can provide valuable insights into the functional epidemiological role of wildlife populations. Rather than establishing transmission routes, our aim is to propose a scalable and non-invasive surveillance framework that identifies priority species and areas for epidemiological monitoring in complex ecological systems. Significance StatementMonitoring disease circulation in wildlife is often hindered by the difficulty of collecting epidemiological data. We propose a novel non-invasive approach that combines species interaction networks derived from camera-trap data with non-invasive antibody detection to explore the exposure patterns of large herbivore communities to foot-and-mouth disease virus (FMDV). By linking the position of species in contact networks with their immunological status, we demonstrate the potential of using ecological centrality as a proxy for identifying key hosts in transmission or indicator species for pathogen circulation. Beyond FMDV, this framework can be adapted to other pathogens for which non-invasive immunological assays are currently being developed, making it broadly relevant for wildlife disease surveillance in remote or protected areas.
- organism: multiple species
- assay: proteomics
- research focus: host-pathogen & immune response
- approach: statistical model
- Citations
- 0
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