1. Epidemiology and Global Health
  2. Microbiology and Infectious Disease
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The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria

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Cite this article as: eLife 2019;8:e40845 doi: 10.7554/eLife.40845

Abstract

Individual malaria infections can carry multiple strains of Plasmodium falciparum with varying levels of relatedness. Yet, how local epidemiology affects the properties of such mixed infections remains unclear. Here, we develop an enhanced method for strain deconvolution from genome sequencing data, which estimates the number of strains, their proportions, identity-by-descent (IBD) profiles and individual haplotypes. Applying it to the Pf3k data set, we find that the rate of mixed infection varies from 29% to 63% across countries and that 51% of mixed infections involve more than two strains. Furthermore, we estimate that 47% of symptomatic dual infections contain sibling strains likely to have been co-transmitted from a single mosquito, and find evidence of mixed infections propagated over successive infection cycles. Finally, leveraging data from the Malaria Atlas Project, we find that prevalence correlates within Africa, but not Asia, with both the rate of mixed infection and the level of IBD.

Article and author information

Author details

  1. Sha Joe Zhu

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7566-2787
  2. Jason A Hendry

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Jacob Almagro-Garcia

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Richard D. Pearson

    Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7386-3566
  5. Roberto Amato

    Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. Alistair Miles

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  7. Daniel J Weiss

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  8. Tim CD Lucas

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  9. Michele Nguyen

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  10. Peter W Gething

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  11. Dominic Kwiatkowski

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  12. Gil McVean

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    For correspondence
    gil.mcvean@bdi.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5012-4162

Funding

Wellcome (206194)

  • Jacob Almagro-Garcia

Wellcome (090770)

  • Jacob Almagro-Garcia
  • Richard D. Pearson
  • Roberto Amato
  • Alistair Miles
  • Dominic Kwiatkowski

Wellcome (100956/Z/13/Z)

  • Sha Joe Zhu
  • Gil McVean

Li Ka Shing Foundation (NA)

  • Gil McVean

Wellcome (204911)

  • Jacob Almagro-Garcia
  • Richard D. Pearson
  • Roberto Amato
  • Alistair Miles
  • Dominic Kwiatkowski

Medical Research Council (G0600718)

  • Jacob Almagro-Garcia
  • Richard D. Pearson
  • Roberto Amato
  • Alistair Miles
  • Dominic Kwiatkowski

Department for International Development (M006212)

  • Jacob Almagro-Garcia
  • Richard D. Pearson
  • Roberto Amato
  • Alistair Miles
  • Dominic Kwiatkowski

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Eduardo Franco, McGill University, Canada

Publication history

  1. Received: August 9, 2018
  2. Accepted: July 10, 2019
  3. Accepted Manuscript published: July 12, 2019 (version 1)

Copyright

© 2019, Zhu et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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