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Multilocus microsatellite typing (MLMT) reveals host-related population structure in Leishmania infantum from northeastern Italy.

Gianluca RugnaElena CarraFederica BergaminiMattia CalzolariDaniela SalvatoreFrancesco CorpusWilliam GennariRaffaella BaldelliMassimo FabbiSilvano NataliniFabrizio VitaleStefania VaraniGiuseppe Merialdi
Published in: PLoS neglected tropical diseases (2018)
A peculiar epidemiological situation was observed in northeastern Italy, with the co-circulation of two distinct populations of L. infantum; one population mainly detected in dogs and the other population detected in humans and in a sand fly. While the classical cycle of CanL in Italy fits well into the data obtained for the first population, the population found in infected humans exhibits a different cycle, probably not involving a canine reservoir. This study can contribute to a better understanding of the population structure of L. infantum circulating in northeastern Italy, thus providing useful epidemiologic information for public health authorities.
Keyphrases
  • public health
  • healthcare
  • machine learning
  • electronic health record
  • genetic diversity
  • health information
  • big data
  • deep learning
  • global health