PLoS Pathogens (Mar 2021)

Combining viral genetic and animal mobility network data to unravel peste des petits ruminants transmission dynamics in West Africa.

  • Arnaud Bataille,
  • Habib Salami,
  • Ismaila Seck,
  • Modou Moustapha Lo,
  • Aminata Ba,
  • Mariame Diop,
  • Baba Sall,
  • Coumba Faye,
  • Mbargou Lo,
  • Lanceï Kaba,
  • Youssouf Sidime,
  • Mohamed Keyra,
  • Alpha Oumar Sily Diallo,
  • Mamadou Niang,
  • Cheick Abou Kounta Sidibe,
  • Amadou Sery,
  • Martin Dakouo,
  • Ahmed Bezeid El Mamy,
  • Ahmed Salem El Arbi,
  • Yahya Barry,
  • Ekaterina Isselmou,
  • Habiboullah Habiboullah,
  • Abdellahi Salem Lella,
  • Baba Doumbia,
  • Mohamed Baba Gueya,
  • Caroline Coste,
  • Cécile Squarzoni Diaw,
  • Olivier Kwiatek,
  • Geneviève Libeau,
  • Andrea Apolloni

DOI
https://doi.org/10.1371/journal.ppat.1009397
Journal volume & issue
Vol. 17, no. 3
p. e1009397

Abstract

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Peste des petits ruminants (PPR) is a deadly viral disease that mainly affects small domestic ruminants. This disease threaten global food security and rural economy but its control is complicated notably because of extensive, poorly monitored animal movements in infected regions. Here we combined the largest PPR virus genetic and animal mobility network data ever collected in a single region to improve our understanding of PPR endemic transmission dynamics in West African countries. Phylogenetic analyses identified the presence of multiple PPRV genetic clades that may be considered as part of different transmission networks evolving in parallel in West Africa. A strong correlation was found between virus genetic distance and network-related distances. Viruses sampled within the same mobility communities are significantly more likely to belong to the same genetic clade. These results provide evidence for the importance of animal mobility in PPR transmission in the region. Some nodes of the network were associated with PPRV sequences belonging to different clades, representing potential "hotspots" for PPR circulation. Our results suggest that combining genetic and mobility network data could help identifying sites that are key for virus entrance and spread in specific areas. Such information could enhance our capacity to develop locally adapted control and surveillance strategies, using among other risk factors, information on animal mobility.