Résumé
1. Within complex ecological systems, identifying animal species likely to
play a key role in the emergence of infectious zoonotic diseases remains a
major challenge. One approach consists of using information on current
ecological and parasitological similarities among host species in order to
predict the most likely pathways for future pathogen spillover. 2. Using
field data acquired from 15 sympatric rodent species in various habitats
in Thailand, Cambodia and Laos, we built networks based on shared
parasites (17 helminth and 15 microparasite species) and shared habitats
among rodent species and humans. We investigated the architectures of
bipartite and unipartite networks using modularity, subgroups partitioning
or node centrality, to assess the relative epidemiological importance of
particular rodent species. 3. Our results showed that Rattus tanezumi,
Bandicota savilei and R. exulans were consistently found to be members of
subgroups that included humans in unipartite and bipartite networks on
zoonotic agents and shared habitats. High values of centrality in shared
zoonotic agents were found for the same three rodent species, whereas high
values of shared habitats were observed for two of them. Although
phylogenetically related rodent species likely shared both habitats and
parasites, a lack of habitat specialisation was associated with increased
zoonotic parasite sharing. 4. Our results emphasize the disproportionate
importance of these three rodent species, through their high degree of
connectivity with humans, which may represent a high risk for direct
zoonotic spillover. Moreover, due to its high centrality in habitats, R.
tanezumi may also play a key role as a bridge host. 5. The recent
discovery of new arenaviruses in rodents in Southeast Asia, with
associated disease in humans in Cambodia, provides an opportunity to test
this empirically. The three rodent species identified using our network
approach are some of the potential maintenance hosts for these new
emerging arenaviruses. 6. Synthesis and applications. Our results on
rodents and their pathogens in Southeast Asia show that network analysis
has a high potential to improve the surveillance of emerging zoonotic
pathogens by targeting key host species and potential “emerging’
pathogen–rodent interactions in complex and heterogeneous landscapes.