Evaluating the performance of malaria genomics for inferring changes in transmission intensity using transmission modelling

Abstract

21Advances in genetic sequencing and accompanying methodological approaches have resulted in 22 pathogen genetics being used in the control of infectious diseases. To utilise these methodologies for 23 malaria we first need to extend the methods to capture the complex interactions between parasites, 24 human and vector hosts, and environment. Here we develop an individual-based transmission model 25 to simulate malaria parasite genetics parameterised using estimated relationships between 26 complexity of infection and age from 5 regions in Uganda and Kenya. We predict that cotransmission 27 and superinfection contribute equally to within-host parasite genetic diversity at 11.5% PCR 28 prevalence, above which superinfections dominate. Finally, we characterise the predictive power of 29 six metrics of parasite genetics for detecting changes in transmission intensity, before grouping them 30in an ensemble statistical model. The best performing model successfully predicted malaria 31 prevalence with mean absolute error of 0.055, suggesting genetic tools could be used for monitoring 32 the impact of malaria interventions. 33 34 Molecular tools are increasingly being used to understand the transmission histories and phylogenies 35 of infectious pathogens 1 . Using phylodynamic methods it is now possible to estimate the historic 36 prevalence of infection directly from molecular data, even in organisms with relatively complex 37 lifecycles 2 . However, these tools typically rely on pathogens having an elevated mutation rate and not 38 undergoing sexual recombination, which allows for the application of coalescent theory 3 . 39Consequently, these techniques are yet to be adapted for the study of P. falciparum malaria, which is 40 known to undergo frequent sexual recombination. In addition, malaria transmission between both the 41 human and the mosquito hosts involves a series of population bottlenecks 4,5 , which combined with 42 the brief sexual stage involving a single two-step meiotic division 6 , have marked effects on the 43 population genetics of P. falciparum 7,8 . This is extenuated by evidence of cotransmission of multiple 44 clonally related parasites 9 , which combined with host mediated immune 10,11 and density-dependent 45 regulation of superinfection 12,13 result in a complicated network of processes driving the genetic 46 diversity of the parasite population within an individual host. 47Despite this substantial complexity, an increasingly nuanced understanding of the processes shaping 48 parasite genetic diversity is appearing, with multiple genetic metrics proving promising for inferring 49 transmission intensity 14,15 . For example, measures of the multiplicity of P. falciparum infections have 50 been shown to be useful for identifying hotspots of malaria transmission 16,17 . The spatial connectivity 51 of parasite populations has also been shown to be well predicted by pairwise measures of identity-by-52 descent 18,19 . More recently, it has been shown that malaria genotyping could be used to enhance...