Malaria Journal (Aug 2020)

Genetic evidence for imported malaria and local transmission in Richard Toll, Senegal

  • Rachel F. Daniels,
  • Stephen F. Schaffner,
  • Yakou Dieye,
  • Gnagna Dieng,
  • Michael Hainsworth,
  • Fatou B. Fall,
  • Coumba Ndoffene Diouf,
  • Medoune Ndiop,
  • Moustapha Cisse,
  • Alioune Badara Gueye,
  • Oumar Sarr,
  • Philippe Guinot,
  • Awa B. Deme,
  • Amy K. Bei,
  • Mouhamad Sy,
  • Julie Thwing,
  • Bronwyn MacInnis,
  • Duncan Earle,
  • Caterina Guinovart,
  • Doudou Sene,
  • Daniel L. Hartl,
  • Daouda Ndiaye,
  • Richard W. Steketee,
  • Dyann F. Wirth,
  • Sarah K. Volkman

DOI
https://doi.org/10.1186/s12936-020-03346-x
Journal volume & issue
Vol. 19, no. 1
pp. 1 – 8

Abstract

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Abstract Background Malaria elimination efforts can be undermined by imported malaria infections. Imported infections are classified based on travel history. Methods A genetic strategy was applied to better understand the contribution of imported infections and to test for local transmission in the very low prevalence region of Richard Toll, Senegal. Results Genetic relatedness analysis, based upon molecular barcode genotyping data derived from diagnostic material, provided evidence for both imported infections and ongoing local transmission in Richard Toll. Evidence for imported malaria included finding that a large proportion of Richard Toll parasites were genetically related to parasites from Thiès, Senegal, a region of moderate transmission with extensive available genotyping data. Evidence for ongoing local transmission included finding parasites of identical genotype that persisted across multiple transmission seasons as well as enrichment of highly related infections within the households of non-travellers compared to travellers. Conclusions These data indicate that, while a large number of infections may have been imported, there remains ongoing local malaria transmission in Richard Toll. These proof-of-concept findings underscore the value of genetic data to identify parasite relatedness and patterns of transmission to inform optimal intervention selection and placement.

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