| Literature DB >> 31298657 |
Sha Joe Zhu1, Jason A Hendry1, Jacob Almagro-Garcia1,2,3,4, Richard D Pearson2,3,4, Roberto Amato2,3,4, Alistair Miles1,2,3,4, Daniel J Weiss1, Tim Cd Lucas1, Michele Nguyen1, Peter W Gething1, Dominic Kwiatkowski1,2,3,4, Gil McVean1,3.
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.Entities:
Keywords: P. falciparum; epidemiology; genome; global health; infectious disease; malaria; microbiology; relatedness
Mesh:
Year: 2019 PMID: 31298657 PMCID: PMC6684230 DOI: 10.7554/eLife.40845
Source DB: PubMed Journal: Elife ISSN: 2050-084X Impact factor: 8.140