The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria

Individual malaria infections can carry multiple strains of Plasmodium falciparum with varying levels of relatedness. Yet, how parameters of local epidemiology affect the rate and relatedness 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. By applying it to the Pf3k data set, we find that the rate of mixed infection varies from 18% to 63% across countries and that 51% of all mixed infections involve more than two strains. Furthermore, we estimate that 55% of 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 with both the rate of mixed infection and the level of IBD.