ArticleWellcome open research2024
Modelling transmission dynamics and genomic diversity in a recombining parasite population.
Article in Wellcome open research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Parasite population dynamics shaped P. falciparum pfhrp2 and pfhrp3 deletion expansion in the Peruvian Amazon.Scientific reports · 2026Article
- Rare variation in malaria parasites biases population-genetic inference.bioRxiv : the preprint server for biology · 2026Article
- Effects of recombination on multi-drug resistance evolution in Plasmodium falciparum malaria.PLoS computational biology · 2025Article
- Detecting imported malaria infections in endemic settings using molecular surveillance: current state and challenges.Frontiers in epidemiology · 2025Review
- Pf8: an open dataset ofWellcome open research · 2025Article
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1 author.
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Abstract
The genomic diversity of a parasite population is shaped by its transmission dynamics but superinfection, cotranmission and recombination make this relationship complex and hard to analyse. This paper aims to simplify the problem by introducing the concept of a genomic transmission graph with three basic parameters: the effective number of hosts, the quantum of transmission and the crossing rate of transmission chains. This enables rapid simulation of coalescence times in a recombining parasite population with superinfection and cotransmission, and it also provides a mathematical framework for analysis of within-host variation. Taking malaria as an example, we use this theoretical model to examine how transmission dynamics and migration affect parasite genomic diversity, including the effective recombination rate and haplotypic metrics of recent common ancestry. We show how key transmission parameters can be inferred from deep sequencing data and as a proof of concept we estimate the Plasmodium falciparum transmission bottleneck. Finally we discuss the potential applications of this novel inferential framework in genomic surveillance for malaria control and elimination. Online tools for exploring the genomic transmission graph are available at d-kwiat.github.io/gtg.
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