Coupling genetic and epidemiological dynamics to unravel parasite structure in transmission gradients

Abstract

Understanding the genetic structure of Plasmodium falciparum populations, the parasite responsible for malaria, is crucial for developing effective disease control and eradication strategies. In this study, we aimed to investigate how populations, epidemiological conditions, and transmission patterns define the evolutionary trajectories of these parasites. To address this question, we developed a stochastic agent-based model that combines disease transmission's genetic and epidemiological dynamics. This allows us to assess how population genetic structure is shaped by varying initial genetic diversity and biting rates. In addition, we discovered that the initial genetic diversity of the population had a modulating effect on the genetic response of the populations, serving as a factor that either maintains or reduces population genetic distance, as well as generating diversity within the population. Our findings highlight the importance of these dual analyses that incorporate genetic dynamics into the disease transmission process, aiming to establish a platform where sequenced parasite genomes can be used to understand these populations' evolutionary status and genetic exchange.