Impact of mosquito gene drive on malaria elimination in a computational model with explicit spatial and temporal dynamics

Abstract

The renewed effort to eliminate malaria and permanently remove its tremendous burden highlights questions of what combination of tools would be sufficient in various settings and what new tools need to be developed. Gene drive mosquitoes constitute a promising set of tools, with multiple different possible approaches including population replacement with introduced genes limiting malaria transmission, driving-Y chromosomes to collapse a mosquito population, and gene drive disrupting a fertility gene and thereby achieving population suppression or collapse. Each of these approaches has had recent success and advances under laboratory conditions, raising the urgency for understanding how each could be deployed in the real world and the potential impacts of each. New analyses are needed as existing models of gene drive primarily focus on nonseasonal or nonspatial dynamics. We use a mechanistic, spatially explicit, stochastic, individual-based mathematical model to simulate each gene drive approach in a variety of sub-Saharan African settings. Each approach exhibits a broad region of gene construct parameter space with successful elimination of malaria transmission due to the targeted vector species. The introduction of realistic seasonality in vector population dynamics facilitates gene drive success compared with nonseasonal analyses. Spatial simulations illustrate constraints on release timing, frequency, and spatial density in the most challenging settings for construct success. Within its parameter space for success, each gene drive approach provides a tool for malaria elimination unlike anything presently available. Provided potential barriers to success are surmounted, each achieves high efficacy at reducing transmission potential and lower delivery requirements in logistically challenged settings.

Requirements for Driving Antipathogen Effector Genes into Populations of Disease Vectors by Homing

“…, Wu et al 2016) of the gene drive construct, either of which could be inserted elsewhere in the genome and could spread by natural selection. If no resistant, suppressor, or mutator allele was released, the nuclease will impose a load upon the population, which can lead to population suppression, or even elimination—yet another way to reduce disease transmission (Burt 2003; Deredec et al 2008, 2011; Eckhoff et al 2017). The possibility of eventually combining population suppression and population modification approaches should be considered.…”

A review of progress toward field application of transgenic mosquitocidal entomopathogenic fungi

“…arabiensis to quickly replace entire natural populations of these species. The aim being to limit mosquito populations ( e.g ., by engineering all male offspring) or to spread genes that make the mosquitoes resistant to Plasmodium spp …”

Spatial gene drives and pushed genetic waves

“…11, 2017; 3 raises biosafety concerns [9], and calls for confinement strategies to prevent unintentional escape and spread of the gene drive constructs [22]. While various genetic design or containment strategies have been discussed [9,20,23,24], and a few computational simulations were conducted [17,18,25], the spatial spreading of the gene drive alleles has received less attention.To understand such phenomena in a spatial context, we will exploit a methodology developed by N. Barton and collaborators, originally in an e↵ort to understand adaptation and speciation of diploid sexually reproducing organisms in genetic hybrid zones [26][27][28].We apply these techniques to a spatial generalization of a model of diploid CRISPR/Cas9 population genetics proposed by Unckless et al [29], and highlight two distinct ways in which gene drive alleles can spread spatially. The non-Mendelian (or "super-Mendelian" [30]) population genetics of gene drives are remarkable because individuals homozygous for a gene drive can in fact spread into wild-type populations even if they carry a positive selective disadvantage s. First, for small selective disadvantages (0 < s < 0.5 in our case), the spatial spreading proceeds via a well-known Fisher-Kolmogorov-Petrovsky-Piskunov wave [31,32].…”

“…Remarkably, high conversion rates have already been achieved with the mutagenic chain reaction ("MCR") realized by the CRISPR/Cas9 system [1][2][3] for yeast (c yeast > 0.995) [19], fruit flies (c flies = 0.97) [20] and malaria vector mosquito, Anopheles stephensi with engineered malaria resistance (c raises biosafety concerns [9], and calls for confinement strategies to prevent unintentional escape and spread of the gene drive constructs [22]. While various genetic design or containment strategies have been discussed [9,20,23,24], and a few computational simulations were conducted [17,18,25], the spatial spreading of the gene drive alleles has received less attention.…”