title: Landscape genetics highlights the role of bank vole metapopulation dynamics in the epidemiology of Puumala hantavirus.
abstract: Rodent host dynamics and dispersal are thought to be critical for hantavirus epidemiology as they determine pathogen persistence and transmission within and between host populations. We used landscape genetics to investigate how the population dynamics of the bank vole Myodes glareolus, the host of Puumala hantavirus (PUUV), vary with forest fragmentation and influence PUUV epidemiology. We sampled vole populations within the Ardennes, a French PUUV endemic area. We inferred demographic features such as population size, isolation and migration with regard to landscape configuration. We next analysed the influence of M. glareolus population dynamics on PUUV spatial distribution. Our results revealed that the global metapopulation dynamics of bank voles were strongly shaped by landscape features, including suitable patch size and connectivity. Large effective size in forest might therefore contribute to the higher observed levels of PUUV prevalence. By contrast, populations from hedge networks highly suffered from genetic drift and appeared strongly isolated from all other populations. This might result in high probabilities of local extinction for both M. glareolus and PUUV. Besides, we detected signatures of asymmetric bank vole migration from forests to hedges. These movements were likely to sustain PUUV in fragmented landscapes. In conclusion, our study provided arguments in favour of source-sink dynamics shaping PUUV persistence and spread in heterogeneous, Western European temperate landscapes. It illustrated the potential contribution of landscape genetics to the understanding of the epidemiological processes occurring at this local scale.
authors.affiliation: INRA, UMR CBGP, Campus international de Baillarguet, CS 30016, F-34988 Montferrier-sur-Lez Cedex, France.
authors.forename: E
authors.initials: E
authors.lastname: Guivier
authors.forename: M
authors.initials: M
authors.lastname: Galan
authors.forename: Y
authors.initials: Y
authors.lastname: Chaval
authors.forename: A
authors.initials: A
authors.lastname: Xuéreb
authors.forename: A
authors.initials: A
authors.lastname: Ribas Salvador
authors.forename: M-L
authors.initials: ML
authors.lastname: Poulle
authors.forename: L
authors.initials: L
authors.lastname: Voutilainen
authors.forename: H
authors.initials: H
authors.lastname: Henttonen
authors.forename: N
authors.initials: N
authors.lastname: Charbonnel
authors.forename: J F
authors.initials: JF
authors.lastname: Cosson
mesh_terms: D000818:Animals; D003411:Arvicolinae / Q000235:genetics* / Q000821:virology*; D001499:Bayes Theorem; D016000:Cluster Analysis; D004247:DNA / Q000302:isolation & purification; D017753:Ecosystem; D005602:France / Q000453:epidemiology; D040961:Genetic Drift; D006480:Hemorrhagic Fever with Renal Syndrome / Q000453:epidemiology* / Q000635:transmission / Q000662:veterinary; D011156:Population Density; D011157:Population Dynamics; D015995:Prevalence; D029262:Puumala virus / Q000472:pathogenicity*; D014197:Trees
chemical_list: D004247:DNA