Skip to main navigation Skip to search Skip to main content

Prediction and Prevention of Parasitic Diseases Using a Landscape Genomics Framework

Research output: Contribution to journalReview articlepeer-review

Abstract

Substantial heterogeneity exists in the dispersal, distribution and transmission of parasitic species. Understanding and predicting how such features are governed by the ecological variation of landscape they inhabit is the central goal of spatial epidemiology. Genetic data can further inform functional connectivity among parasite, host and vector populations in a landscape. Gene flow correlates with the spread of epidemiologically relevant phenotypes among parasite and vector populations (e.g., virulence, drug and pesticide resistance), as well as invasion and re-invasion risk where parasite transmission is absent due to current or past intervention measures. However, the formal integration of spatial and genetic data (‘landscape genetics’) is scarcely ever applied to parasites. Here, we discuss the specific challenges and practical prospects for the use of landscape genetics and genomics to understand the biology and control of parasitic disease and present a practical framework for doing so.

Original languageEnglish
Pages (from-to)264-275
Number of pages12
JournalTrends in Parasitology
Volume33
Issue number4
DOIs
StatePublished - 1 Apr 2017

Bibliographical note

Publisher Copyright:
© 2016 Elsevier Ltd

Funding

FundersFunder number
National Institute of Allergy and Infectious DiseasesR15AI105749

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 2 - Zero Hunger
      SDG 2 Zero Hunger
    2. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being
    3. SDG 15 - Life on Land
      SDG 15 Life on Land

    Fingerprint

    Dive into the research topics of 'Prediction and Prevention of Parasitic Diseases Using a Landscape Genomics Framework'. Together they form a unique fingerprint.

    Cite this