Vector genetics, insecticide resistance and gene drives: an agent-based modeling approach to evaluate malaria transmission and elimination

Abstract

Vector control has been a key component in the fight against malaria for decades, and chemical insecticides are critical to the success of vector control programs worldwide. However, increasing resistance to insecticides threatens to undermine these efforts. Understanding the evolution and propagation of resistance is thus imperative to mitigating loss of intervention effectiveness. Additionally, accelerated research and development of new tools that can be deployed alongside existing vector control strategies is key to eradicating malaria in the near future. Methods such as gene drives that aim to genetically modify large mosquito populations in the wild to either render them refractory to malaria or impair their reproduction may prove invaluable tools. Mathematical models of gene flow in populations, which is the transfer of genetic information from one population to another through migration, can offer invaluable insight into the behavior and potential impact of gene drives as well as the spread of insecticide resistance in the wild. Here, we present the first multi-locus, agent-based model of vector genetics that accounts for mutations and a many-to-many mapping cardinality of genotypes to phenotypes to investigate gene flow, and the propagation of gene drives in Anopheline populations. This model is embedded within a large scale individual-based model of malaria transmission representative of a high burden, high transmission setting characteristic of the Sahel. Results are presented for the selection of insecticide-resistant vectors and the spread of resistance through repeated deployment of insecticide treated nets (ITNs), in addition to scenarios where gene drives act in concert with existing vector control tools such as ITNs. The roles of seasonality, spatial distribution of vector habitat and feed sites, and existing vector control in propagating alleles that confer phenotypic traits via gene drives that result in reduced transmission are explored. The ability to model a spectrum of vector species with different genotypes and phenotypes in the context of malaria transmission allows us to test deployment strategies for existing interventions that reduce the deleterious effects of resistance and allows exploration of the impact of new tools being proposed or developed.Author summaryVector control interventions are essential to the success of global malaria control and elimination efforts but increasing insecticide resistance worldwide threatens to derail these efforts. Releasing genetically modified mosquitoes that use gene drives to pass on desired genes and their associated phenotypic traits to the entire population within a few generations has been proposed to address resistance and other issues such as transmission heterogeneity that can sustain malaria transmission indefinitely. While the ethics and safety of these methods are being debated, mathematical models offer an efficient way of predicting the behavior and estimating the efficacy of these interventions if deployed to specific regions facing challenges to reaching elimination. We have developed a detailed mathematical model of vector genetics where specific genomes code for physical attributes that influence transmission and are affected by the surrounding environment. This is the first model to incorporate an individual-based multi-locus genetic model into a detailed individual-based model of malaria transmission. This model opens the door to investigate a number of subtle but important questions such as the effects of small numbers of mosquitoes in a region sustaining malaria transmission during the low transmission season, and the success of gene drives in regions where extant vector control interventions could kill off gene drive mosquitoes before establishment. Here, we investigate the reduced efficacy of current vector control measures in the presence of insecticide resistance and evaluate the likelihood of achieving local malaria elimination using gene drive mosquitoes released into a high transmission setting alongside other vector control measures.

Reversing insecticide resistance with allelic-drive in Drosophila melanogaster

“…Multiple models and studies have established significant decrements in LLINs efficacy due to increasing insecticide resistance. These models also indicate that efficacy of current vector control methods 47 , 48 could be preserved if the prevalence of IR was maintained below 30%, which we surpassed (<15% IR) in cage experiments of lab populations. However, the variability in natural populations could impact the efficacy of the drive if a common variant target site allele were present in the target population.…”

Modeling impact and cost‐effectiveness of driving‐Y gene drives for malaria elimination in the Democratic Republic of the Congo

“…The model dynamically simulates vector‐human and human‐vector transmissions during blood meals. Driving‐Y is one of several gene drive strategies that can be simulated within EMOD (Selvaraj et al, 2020).…”

Gene Drive Mosquitoes Can Aid Malaria Elimination by Retarding Plasmodium Sporogonic Development

“…We include baseline health seeking for symptomatic cases as an intervention where human agents can seek treatment with artemether-lumefantrine (AL) 80% of the time within 2 days of severe symptom onset and 50% of the time within 3 days of the onset of a clinical but non-severe case. Mosquitoes within EMOD contain simulated genomes that can model up to 10 genes with 8 alleles per gene with phenotypic traits that map onto different genotypes ( 49 ). Here we modelled an integral gene drive system ( 57 ) aimed at population replacement with an effector that results in delayed sporozoite production in infected mosquitoes as well as an overall reduction in the number of sporozoites produced by infected mosquitoes.…”

“…Finally, we predicted how deployment of the MM-CP effector trait would modify malaria epidemiology using a mechanistic, agent-based model of P. falciparum transmission that includes vector life cycle and within-host parasite and immune dynamics. The model is based on the EMOD framework that has recently been updated to enable the simulation of gene drives ( 49 ). There remain knowledge gaps that preclude a direct translation of experimental entomological or molecular data into epidemiological parameters, for example linking the observed reduction in sporozoite DNA and its quantitative effect on onward transmission.…”