A rare example of long-term elimination of Aedes aegypti occurred in Brisbane, where legislatively enforced removal of rainwater tanks led to its disappearance by the mid-1950s. However, widespread tank installation during a later drought reintroduced critical breeding habitat, enabling persistence in this subtropical region. With Ae. aegypti re-invading towns ~150 km north of Brisbane, we assessed the potential for sustained elimination. Using a genomics-informed simulation modeling framework, we integrated population genomic inference of connectivity and migration with entomological and environmental data to parameterize elimination scenarios. Genomic analyses revealed strong overall isolation among neighbouring populations in the region, with limited recent migration detected between the two southernmost populations, in Murgon and Wondai. We therefore focused simulations on these populations. Our results indicate that elimination is feasible with moderate releases of incompatible Wolbachia-infected (IIT) males (sorting error ≤ 10−6), provided non-compliant rainwater tanks are removed first. This combined strategy achieved >99% suppression and elimination in 35% of simulations in one town, whereas IIT alone resulted in moderate suppression (61–93%) and increased the risk of Wolbachia establishment at higher release ratios.

Close-kin mark-recapture (CKMR) methods have recently been used to infer demographic parameters for several aquatic and terrestrial species. For mosquitoes, the spatial distribution of close-kin pairs has been used to estimate mean dispersal distance, of relevance to vector-borne disease transmission and genetic biocontrol strategies. Close-kin methods have advantages over traditional mark-release-recapture (MRR) methods as the mark is genetic, removing the need for physical marking and recapturing that may interfere with movement behavior. Here, we extend CKMR methods to accommodate spatial structure alongside life history for mosquitoes and comparable insects. We derive kinship probabilities for parent-offspring and full-sibling pairs in a spatial context, where an individual in each pair may be a larva or adult. Using the dengue vector Aedes aegypti as a case study, we use an individual-based model of mosquito life history to test the effectiveness of this approach at estimating parameters such as mean dispersal distance, daily staying probability, and the strength of a barrier to movement. Considering a simulated population of 9,025 adult mosquitoes arranged on a 19-by-19 grid, we find the CKMR approach provides unbiased and precise estimates of mean dispersal distance given a total of 2,500 adult females sampled over a three-month period using 25 traps evenly spread throughout the landscape. The CKMR approach is also able to estimate parameters of more complex dispersal kernels, such as the daily staying probability of a zero-inflated exponential kernel, or the strength of a barrier to movement, provided the magnitude of these parameters is greater than 0.5. These results suggest that CKMR provides an insightful characterization of mosquito dispersal that is complementary to conventional MRR methods.

Agent-based models (ABMs) simulate the formation and evolution of social processes at a fundamental level by decoupling agent behavior from global observations. In the case where ABM networks evolve over time as a result of (or in conjunction with) agent states, there is a need for understanding the relationship between the dynamic processes and network structure. Social networks provide a natural set of tools for understanding the emergent relationships of these systems. This work examines the utility of a collection of network comparison methods for the purpose of tracking network changes in an ABM over time or between model parameters. Among the techniques examined is a novel graph pseudometric based on heat content asymptotics, which have been shown to distinguish many isospectral graphs which are not isomorphic. Additionally, we establish the use of observations about real-world networks from network science (e.g. fat-tailed degree distribution, small-world property) for ABM validation in the case where empirical population data is unavailable. These methods are all demonstrated on systematic perturbations of an original model simulating the formation of friendships in a population of 20,000 agents in Cincinnati, OH.

Objective The MGDrivE (MGDrivE 1 and MGDrivE 2) modeling framework provides a flexible and expansive environment for testing the efficacy of novel gene-drive constructs for the control of mosquito-borne diseases. However, the existing model framework did not previously support several features necessary to simulate some types of intervention strategies. Namely, current MGDrivE versions do not permit modeling of small molecule inducible systems for controlling gene expression in gene drive designs or the inheritance patterns of self-eliminating gene drive mechanisms. Results Here, we demonstrate a new MGDrivE 2 module that permits the simulation of gene drive strategies incorporating small molecule-inducible systems and self-eliminating gene drive mechanisms. Additionally, we also implemented novel sparsity-aware sampling algorithms for improved computational efficiency in MGDrivE 2 and supplied an analysis and plotting function applicable to the outputs of MGDrivE 1 and MGDrivE 2.

Humans learn from the occurrence of events at different places and times to predict similar trajectories of events. We define loosely decoupled time (LDT) phenomena as two or more events that could occur in different places and across different timelines but share similarities in the nature of the event and the properties of the location. In this work, we improve the use of recurrent neural networks (RNN), particularly long short-term memory (LSTM) networks, to enable AI solutions that generate better time series predictions for LDT. We used similarity measures between the time series based on the time series properties detected by the LSTM and introduced embeddings representing these properties. The embeddings represent the properties of the event, which, coupled with the LSTM structure, can be clustered to identify similar temporally unaligned events. In this study, we explore methods of seeding a multivariate LSTM from time-invariant data related to the geophysical and demographic phenomena modeled by the LSTM. We applied these methods to time-series data derived from COVID-19 detected infection and death cases. We use publicly available socioeconomic data to seed the LSTM models, creating embeddings, to determine whether such seeding improves case predictions. The embeddings produced by these LSTMs are clustered to identify the best-matching candidates for forecasting evolving time series. Applying this method, we showed an improvement in the 10-day moving average predictions of disease propagation at the US County level.

The core components of CRISPR-based gene drives, Cas9 and guide RNA (gRNA), either can be linked within a self-contained single cassette (full gene-drive, fGD) or be provided in two separate elements (split gene-drive, sGD), the latter offering greater control options. We previously engineered split systems that could be converted genetically into autonomous full drives. Here, we examine such dual systems inserted at the spo 11 locus that are recoded to restore gene function and thus organismic fertility. Despite minimal differences in transmission efficiency of the sGD or fGD drive elements in single generation crosses, the reconstituted spo 11 fGD cassette surprisingly exhibits slower initial drive kinetics than the unlinked sGD element in multigenerational cage studies, but then eventually catches up to achieve a similar level of final introduction. These unexpected kinetic behaviors most likely reflect differing transient fitness costs associated with individuals co-inheriting Cas9 and gRNA transgenes during the drive process.

In response to the COVID-19 pandemic and the potential threat of future epidemics caused by novel viruses, we developed a flexible framework for modeling disease intervention effects. This tool is intended to aid decision makers at multiple levels as they compare possible responses to emerging epidemiological threats for optimal control and reduction of harm. The framework is specifically designed to be both scalable and modular, allowing it to model a variety of population levels, viruses, testing methods and strategies--including pooled testing--and intervention strategies. In this paper, we provide an overview of this framework and examine the impact of different intervention strategies and their impact on infection dynamics.

A recurring target-site mutation identified in various pests and disease vectors alters the voltage gated sodium channel (vgsc) gene (often referred to as knockdown resistance or kdr) to confer resistance to commonly used insecticides, pyrethroids and DDT. The ubiquity of kdr mutations poses a major global threat to the continued use of insecticides as a means for vector control. In this study, we generate common kdr mutations in isogenic laboratory Drosophila strains using CRISPR/Cas9 editing. We identify differential sensitivities to permethrin and DDT versus deltamethrin among these mutants as well as contrasting physiological consequences of two different kdr mutations. Importantly, we apply a CRISPR-based allelic-drive to replace a resistant kdr mutation with a susceptible wild-type counterpart in population cages. This successful proof-of-principle opens-up numerous possibilities including targeted reversion of insecticide-resistant populations to a native susceptible state or replacement of malaria transmitting mosquitoes with those bearing naturally occurring parasite resistant alleles.

Close-kin mark-recapture (CKMR) methods have recently been used to infer demographic parameters such as census population size and survival for fish of interest to fisheries and conservation. These methods have advantages over traditional mark-recapture methods as the mark is genetic, removing the need for physical marking and recapturing that may interfere with parameter estimation. For mosquitoes, the spatial distribution of close-kin pairs has been used to estimate mean dispersal distance, of relevance to vector-borne disease transmission and novel biocontrol strategies. Here, we extend CKMR methods to the life history of mosquitoes and comparable insects. We derive kinship probabilities for mother-offspring, father-offspring, full-sibling and half-sibling pairs, where an individual in each pair may be a larva, pupa or adult. A pseudo-likelihood approach is used to combine the marginal probabilities of all kinship pairs. To test the effectiveness of this approach at estimating mosquito demographic parameters, we develop an individual-based model of mosquito life history incorporating egg, larva, pupa and adult life stages. The simulation labels each individual with a unique identification number, enabling close-kin relationships to be inferred for sampled individuals. Using the dengue vector Aedes aegypti as a case study, we find the CKMR approach provides unbiased estimates of adult census population size, adult and larval mortality rates, and larval life stage duration for logistically feasible sampling schemes. Considering a simulated population of 3,000 adult mosquitoes, estimation of adult parameters is accurate when ca. 40 adult females are sampled biweekly over a three month period. Estimation of larval parameters is accurate when adult sampling is supplemented with ca. 120 larvae sampled biweekly over the same period. The methods are also effective at detecting intervention-induced increases in adult mortality and decreases in population size. As the cost of genome sequencing declines, CKMR holds great promise for characterizing the demography of mosquitoes and comparable insects of epidemiological and agricultural significance.

CRISPR-based genetic engineering tools aimed to bias sex ratios, or drive effector genes into animal populations, often integrate the transgenes into autosomal chromosomes. However, in species with heterogametic sex chromsomes (e.g. XY, ZW), sex linkage of endonucleases could be beneficial to drive the expression in a sex-specific manner to produce genetic sexing systems, sex ratio distorters, or even sex-specific gene drives, for example. To explore this possibility, here we develop a transgenic line of Drosophila melanogaster expressing Cas9 from the Y chromosome. We functionally characterize the utility of this strain for both sex selection and gene drive finding it to be quite effective. To explore its utility for population control, we built mathematical models illustrating its dynamics as compared to other state-of-the-art systems designed for both population modification and suppression. Taken together, our results contribute to the development of current CRISPR genetic control tools and demonstrate the utility of using sex-linked Cas9 strains for genetic control of animals.

The mosquito Aedes aegypti is the principal vector for arboviruses including dengue/yellow fever, chikungunya, and zika, infecting hundreds of millions of people annually. Unfortunately, traditional control methodologies are insufficient, so innovative control methods are needed. To complement existing measures, here we develop a molecular genetic control system termed precision guided sterile insect technique (pgSIT) in Aedes aegypti . PgSIT uses a simple CRISPR-based approach to generate sterile males that are deployable at any life stage. Supported by mathematical models, we empirically demonstrate that released pgSIT males can compete, suppress, and eliminate mosquitoes in multigenerational population cages. This platform technology could be used in the field, and adapted to many vectors, for controlling wild populations to curtail disease in a safe, confinable, and reversible manner.

A rare example of a successful long-term elimination of the mosquito Aedes aegypti is in Brisbane, Queensland, where the legislatively-enforced removal of rainwater tanks drove its disappearance by the mid-1950s. However, a decade-long drought led to the mass installation of rainwater tanks throughout the region, re-introducing critical breeding sites for the mosquito’s persistence in this subtropical region. With Ae. aegypti re-invading towns just 150 km north of Brisbane, we examined the potential for their sustained elimination. Through genomic analyses, we estimated historical expansion and current isolation between neighboring populations as close as 15 kilometers. The estimated recent migration rate, entomological and meteorological data were used to calibrate the simulations of elimination campaigns in the two southernmost populations. Our simulations indicate that Ae. aegypti could be eliminated with moderate release numbers of incompatible Wolbachia -infected (IIT) males (sorted with an error rate ≤10 -6 ) if non-compliant rainwater tanks are removed first. With this combined campaign, highly effective suppression (>99%) was predicted in both towns, and complete elimination was predicted in 35% of simulations in one town. Without tank removal, however, IIT led to a moderate suppression (61-93%) even with a 40:1 ratio of released IIT males to local males. Moreover, with a ratio of >20:1, Wolbachia establishment was predicted when the sorting error was >10 -7 . Our conservative estimates of intervention outcomes inform the planning of Ae. aegypti elimination in the region, and offer insight into the effective combinations of conventional and novel control tools, particularly for vulnerable mosquito populations at range margins. Significance After decades of range stagnation in Australia, the Aedes aegypti mosquito is expanding southward, approaching the most-densely-populated areas of Queensland. Using population genomics and simulation modeling of elimination campaigns, we show that Australia’s southernmost populations of this disease vector are genetically isolated and could be eliminated with moderate releases of incompatible Wolbachia-infected males if major larval breeding sites (non-compliant rainwater tanks) are removed first. The risk of Wolbachia establishment for this approach is low, and so is the risk of quick mosquito re-invasion. Our conservative estimates of intervention outcomes inform the planning of Ae. aegypti elimination in the region, and offer new insight into the benefits of combining conventional and novel control tools, particularly for mosquito populations at range margins.

CRISPR-based gene-drive systems, which copy themselves via gene conversion mediated by the homology-directed repair (HDR) pathway, have the potential to revolutionize vector control. However, mutant alleles generated by the competing non-homologous end-joining (NHEJ) pathway, resistant to Cas9 cleavage, can interrupt the spread of gene-drive elements. We hypothesized that drives targeting genes essential for viability or reproduction also carrying recoded sequences that restore endogenous gene functionality should benefit from dominantly-acting maternal clearance of NHEJ alleles combined with recessive Mendelian culling processes. Here, we test split gene-drive (sGD) systems in Drosophila melanogaster that are inserted into essential genes required for viability ( rab5 , rab11 , prosalpha2 ) or fertility ( spo11 ). In single generation crosses, sGDs copy with variable efficiencies and display sex-biased transmission. In multigenerational cage trials, sGDs follow distinct drive trajectories reflecting their differential tendencies to induce target chromosome damage and/or lethal/sterile mosaic Cas9-dependent phenotypes, leading to inherently confinable drive outcomes.

Homing-based gene drives, engineered using CRISPR/Cas9, have been proposed to spread desirable genes throughout populations. However, invasion of such drives can be hindered by the accumulation of resistant alleles. To limit this obstacle, we engineer a confinable population modification home-and-rescue (HomeR) drive in Drosophila targeting an essential gene. In our experiments, resistant alleles that disrupt the target gene function were recessive lethal and therefore disadvantaged. We demonstrate that HomeR can achieve an increase in frequency in population cage experiments, but that fitness costs due to the Cas9 insertion limit drive efficacy. Finally, we conduct mathematical modeling comparing HomeR to contemporary gene drive architectures for population modification over wide ranges of fitness costs, transmission rates, and release regimens. HomeR could potentially be adapted to other species, as a means for safe, confinable, modification of wild populations.

Interest in gene drive technology has continued to grow as promising new drive systems have been developed in the lab and discussions are moving towards implementing field trials. The prospect of field trials requires models that incorporate a significant degree of ecological detail, including parameters that change over time in response to environmental data such as temperature and rainfall, leading to seasonal patterns in mosquito population density. Epidemiological outcomes are also of growing importance, as: i) the suitability of a gene drive construct for release will depend on its expected impact on disease transmission, and ii) initial field trials are expected to have a measured entomological outcome and a modeled epidemiological outcome. We present MGDrivE 2 (Mosquito Gene Drive Explorer 2): a significant development from the MGDrivE 1 simulation framework that investigates the population dynamics of a variety of gene drive architectures and their spread through spatially-explicit mosquito populations. Key strengths and fundamental improvements of the MGDrivE 2 framework are: i) the ability of parameters to vary with time and induce seasonal population dynamics, ii) an epidemiological module accommodating reciprocal pathogen transmission between humans and mosquitoes, and iii) an implementation framework based on stochastic Petri nets that enables efficient model formulation and flexible implementation. Example MGDrivE 2 simulations are presented to demonstrate the application of the framework to a CRISPR-based split gene drive system intended to drive a disease-refractory gene into a population in a confinable and reversible manner, incorporating time-varying temperature and rainfall data. The simulations also evaluate impact on human disease incidence and prevalence. Further documentation and use examples are provided in vignettes at the project's CRAN repository. MGDrivE 2 is freely available as an open-source R package on CRAN (https://CRAN.R-project.org/package=MGDrivE2). We intend the package to provide a flexible tool capable of modeling gene drive constructs as they move closer to field application and to infer their expected impact on disease transmission.

CRISPR-Cas9-based gene drive systems possess the inherent capacity to spread progressively throughout target populations. Here we describe two self-copying (or active) guide RNA-only genetic elements, called e-CHACRs and ERACRs. These elements use Cas9 produced in trans by a gene drive either to inactivate the cas9 transgene (e-CHACRs) or to delete and replace the gene drive (ERACRs). e-CHACRs can be inserted at various genomic locations and carry two or more gRNAs, the first copying the e-CHACR and the second mutating and inactivating the cas9 transgene. Alternatively, ERACRs are inserted at the same genomic location as a gene drive, carrying two gRNAs that cut on either side of the gene drive to excise it. e-CHACRs efficiently inactivate Cas9 and can drive to completion in cage experiments. Similarly, ERACRs, particularly those carrying a recoded cDNA-restoring endogenous gene activity, can drive reliably to fully replace a gene drive. We compare the strengths of these two systems.

CRISPR-based gene drives can spread through wild populations by biasing their own transmission above the 50% value predicted by Mendelian inheritance. These technologies offer population-engineering solutions for combating vector-borne diseases, managing crop pests, and supporting ecosystem conservation efforts. Current technologies raise safety concerns for unintended gene propagation. Herein, we address such concerns by splitting the drive components, Cas9 and gRNAs, into separate alleles to form a trans-complementing split–gene-drive (tGD) and demonstrate its ability to promote super-Mendelian inheritance of the separate transgenes. This dual-component configuration allows for combinatorial transgene optimization and increases safety by restricting escape concerns to experimentation windows. We employ the tGD and a small–molecule-controlled version to investigate the biology of component inheritance and resistant allele formation, and to study the effects of maternal inheritance and impaired homology on efficiency. Lastly, mathematical modeling of tGD spread within populations reveals potential advantages for improving current gene-drive technologies for field population modification.

BACKGROUND:The discovery of CRISPR-based gene editing and its application to homing-based gene drive systems has been greeted with excitement, for its potential to control mosquito-borne diseases on a wide scale, and concern, for the invasiveness and potential irreversibility of a release. Gene drive systems that display threshold-dependent behavior could potentially be used during the trial phase of this technology, or when localized control is otherwise desired, as simple models predict them to spread into partially isolated populations in a confineable manner, and to be reversible through releases of wild-type organisms. Here, we model hypothetical releases of two recently engineered threshold-dependent gene drive systems-reciprocal chromosomal translocations and a form of toxin-antidote-based underdominance known as UDMEL-to explore their ability to be confined and remediated.RESULTS:We simulate releases of Aedes aegypti, the mosquito vector of dengue, Zika, and other arboviruses, in Yorkeys Knob, a suburb of Cairns, Australia, where previous biological control interventions have been undertaken on this species. We monitor spread to the neighboring suburb of Trinity Park to assess confinement. Results suggest that translocations could be introduced on a suburban scale, and remediated through releases of non-disease-transmitting male mosquitoes with release sizes on the scale of what has been previously implemented. UDMEL requires fewer releases to introduce, but more releases to remediate, including of females capable of disease transmission. Both systems are expected to be confineable to the release site; however, spillover of translocations into neighboring populations is less likely.CONCLUSIONS:Our analysis supports the use of translocations as a threshold-dependent drive system capable of spreading disease-refractory genes into Ae. aegypti populations in a confineable and reversible manner. It also highlights increased release requirements when incorporating life history and population structure into models. As the technology nears implementation, further ecological work will be essential to enhance model predictions in preparation for field trials.

Malaria, dengue, Zika, and other mosquito-borne diseases continue to pose a major global health burden through much of the world, despite the widespread distribution of insecticide-based tools and antimalarial drugs. The advent of CRISPR/Cas9-based gene editing and its demonstrated ability to streamline the development of gene drive systems has reignited interest in the application of this technology to the control of mosquitoes and the diseases they transmit. The versatility of this technology has also enabled a wide range of gene drive architectures to be realized, creating a need for their population-level and spatial dynamics to be explored. To this end, we present MGDrivE (Mosquito Gene Drive Explorer): a simulation framework designed to investigate the population dynamics of a variety of gene drive architectures and their spread through spatially-explicit mosquito populations. A key strength of the MGDrivE framework is its modularity: a) a genetic inheritance module accommodates the dynamics of gene drive systems displaying user-defined inheritance patterns, b) a population dynamic module accommodates the life history of a variety of mosquito disease vectors and insect agricultural pest species, and c) a landscape module accommodates the distribution of insect metapopulations connected by migration in space. Example MGDrivE simulations are presented to demonstrate the application of the framework to CRISPR/Cas9-based homing gene drive for: a) driving a disease-refractory gene into a population (i.e. population replacement), and b) disrupting a gene required for female fertility (i.e. population suppression), incorporating homing-resistant alleles in both cases. We compare MGDrivE with other genetic simulation packages, and conclude with a discussion of future directions in gene drive modeling.