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Research interests

Research projects

Gene drives modelling: a decision support tool for new target species

Gene drives constitute a novel and potentially ground breaking set of approaches for the control of undesirable species, or the introduction of desirable traits into wild population. Such genetic control strategies are already being actively developed in several species (like rodents and mosquitoes), and there is strong interest in applying these techniques to a wide range of species in various domains, including agriculture, health, conservation and biosecurity. There remains however considerable uncertainty regarding the feasibility and efficacy of gene drives in various species, based on genomic, genetic and ecological specificities of each target species. As a Research Scientist at CSIRO, my main objective was to create and develop a decision support tool to assess the potential of gene drives as a new control method for these new target species.

DriverSEAT: A spatially-explicit gene drive modelling framework

The theoretical framework we developed, named DriverSEAT, is a new spatial, modular modelling framework designed to assess the outcome of gene drives in a range of target species based on their specific ecological dynamics and genetics. DriverSEAT was designed as a versatile and highly modular model and can simulate the dynamics of two interacting species, whether they be plants, insects, vertebrates, fungi, or other potential target species. In our initial publication we provide a detailed presentation of this model, as well as an example of its application on scenarios of genetic control of weeds, a potential candidate for gene drive control that presents significant challenges associated with plant population dynamics.

Gene drives as a potential control method in agriculture

Expanding on the development of this decision support tool, and in collaboration with CSIRO colleagues from Agriculture and Food and Health and Biosecurity, we also published several articles on the potential use of gene drives in agricultural settings. In particular, we focused on potential applications in plants for the control of agriculturally significant weeds, an approach that is especially challenging given genetic, genomic and ecological specificities of plants and plant populations. We also investigated the specificities of agricultural environments, and the challenges and opportunities they provide for a potential deployment of gene drive as a control method (see Pulications page).

Evolution of drug resistance in malaria

Current malaria control efforts rely primarily on two pillars: chemotherapy and vector control. Several drugs have been and are currenly used as treatment for patients infected with Plasmodium parasites, but resistant parasites strains have been observed in each case and pose a significant threat to the sustainability of malaria drug treatments.

My objective is to study the theoretical basis of resistance emergence and evolution in Plasmodium parasites in relevant ecological contexts, with the ultimate goal of informing control policies to achieve optimal levels of disease reduction while limiting the potential for selection of resistance.

A modeling framework combining within-host and between-hosts dynamics

Resistant and sensitive strains of Plasmodium may be subjected to different selective pressures, operating at various scales: within-host, where strains may differ in their infectivity, their sensitivity to host immune factors and their response to treatment, as well as between-hosts, with potential differences in transmissibility, incubation periods and clearance rates. To better understand the impact of these various selective pressures on the evolution of resistance, I constructed a modeling framework that operates across biological scales, both within- and between-hosts. This model simulates the dynamics of co-circulating sensitive and resistant malaria strains, their transmission between human hosts and mosquito vectors and the course of (multiple) infection(s) within each of these hosts.

Focusing first on the interaction between epidemiological dynamics and within-human course of infection, this modeling framework reveals important patterns of selective effects across these scales. As an example, while there is a known trade-off for all control efforts between reducing disease incidence and favoring resistant strains, treatment coverage (among hosts) was shown to have a stronger impact on reducing disease, whereas treatment efficacy (within a treated host) appeared to select more strongly for resistance strains. This finding suggests that treatment coverage should constitute the primary focus of large-scale control efforts.

The impacts of vector factors on the evolution of drug resistance

Additionally, using that same modeling framework, I also focus on the impacts of within-vector dynamics on the evolution of drug resistant strains. Plasmodium populations go through strong bottlenecks within their mosquito vector, and I describe how this bottleneck impacts resistance evolution in various eco-epidemiological settings, and depending on the existence of within-vector costs of resistance. I also study interactions between vector control strategies and drug resistance evolution, with potentially crucial consequences for integrated malaria control strategies that often rely on a combination of both approaches.

Aedes aegypti population modelling and dengue control

My research goals at NCSU and UC Davis were to build and develop spatially- and biologically-explicit models of Aedes aegypti populations, in order to predict the success of vector control programs in a given location, both in terms of mosquito population control and reduction of dengue incidence. In particular, one objective of this project is to evaluate the strategies based on the release of transgenic mosquitoes, and to provide guidelines on the optimal approaches to achieve population suppression or population replacement.

Skeeter Buster, a spatial model of Aedes aegypti population dynamics and genetics

The major component of this project is a detailed, stochastic, weather-driven model of Ae. aegypti populations, called Skeeter Buster. This model incorporates many specific aspects of Ae. aegypti development, life history and behavior, as well as an explicit spatial setup that operates at the level of individual houses, and, within each house, of individual containers in which immature cohorts are modeled. Skeeter Buster provides a realistic model of a specific mosquito population that can be used to predict the outcome of various control strategies, whether they are based on traditional approaches or on genetic methods, or a combination of the above.

For details on the features and main results of Skeeter Buster, refer to the presentation paper in PLoS NTDs. This model is distributed as free software under a GPL license; see the Skeeter Buster website.

Case studies – Model calibration and validation

The primary case study for Skeeter Buster was carried out on the Ae. aegypti population in the city of Iquitos, Peru. This study demonstrated that the model, specifically calibrated to this location, faithfully replicates field observations on the natural population, including stage-specific densities and spatial heterogeneities.

Applications of Skeeter Buster to several other cases, including locations in Australia, Vietnam, Argentina, Mexico and the United States, have been or are currently under study.

Genetic control strategies – Population suppression and replacement

Skeeter Buster, as a biologically detailed, spatially explicit population dynamics and genetics model, is a primary tool to evaluate the potential success and guide the development of optimal strategies for releasing transgenic mosquitoes into a natural population. A number of specific strategies can be simulated using this model.

My research focused more particularly on strategies of population suppression using female-killing genetic constructs, and strategies of population replacement (replacing a native, competent population with an engineered, non-competent strain), based on the use of genetic constructs (MEDEA, Killer/Rescue) or infection by bacterial agents (Wolbachia).

Epidemiological model and control of dengue transmission

Skeeter Buster can provide predictions on the effects of various control strategies on the resident mosquito populations. Naturally the ultimate objective of these control approaches is to reduce the human incidence of diseases vectored by Ae. aegypti, most particularly dengue. To that end I also contributed to the development of an epidemiological model that describes the transmission of dengue in a human population based on the vector population dynamics as they are modeled by Skeeter Buster. This epidemiological model shares the general characteristics and level of spatial detail of Skeeter Buster, and translates the results of a vector control method in terms of human dengue incidence.


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Research interests

Research projects

Gene drives in new species

Gene drives and agriculture

Malaria and drug resistance

Modeling across scales
Vector factors

Dengue and genetic control

Skeeter Buster
Case studies
Genetic vector control
Epidemiological modeling